Add GitHub ML run 20261017T130557000000Z-152e3feb

coverage/20261017T130557000000Z-152e3feb.json

@@ -0,0 +1,88 @@
+{
+  "complete_sweep": true,
+  "queries": [
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"machine learning\" in:name,description,readme pushed:2026-10-01T23:59:54Z..2026-10-01T23:59:57Z",
+      "query_id": "recall.name.machine-learning",
+      "range_end": "2026-10-01T23:59:57Z",
+      "range_start": "2026-10-01T23:59:54Z",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 1
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"machine learning\" in:name,description,readme pushed:2026-10-01T23:59:57Z..2026-10-01",
+      "query_id": "recall.name.machine-learning",
+      "range_end": "2026-10-01",
+      "range_start": "2026-10-01T23:59:57Z",
+      "search_limit_reached": true,
+      "status": "partitioned",
+      "total_count": 7790
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"machine learning\" in:name,description,readme pushed:2026-10-01T23:59:57Z..2026-10-01T23:59:58Z",
+      "query_id": "recall.name.machine-learning",
+      "range_end": "2026-10-01T23:59:58Z",
+      "range_start": "2026-10-01T23:59:57Z",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"machine learning\" in:name,description,readme pushed:2026-10-01T23:59:58Z..2026-10-01",
+      "query_id": "recall.name.machine-learning",
+      "range_end": "2026-10-01",
+      "range_start": "2026-10-01T23:59:58Z",
+      "search_limit_reached": true,
+      "status": "partitioned",
+      "total_count": 7790
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"machine learning\" in:name,description,readme pushed:2026-10-01T23:59:58Z..2026-10-01T23:59:59Z",
+      "query_id": "recall.name.machine-learning",
+      "range_end": "2026-10-01T23:59:59Z",
+      "range_start": "2026-10-01T23:59:58Z",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 1
+    },
+    {
+      "coverage_gap": true,
+      "coverage_gap_reason": "GitHub Search limits a query to 1,000 results",
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"machine learning\" in:name,description,readme pushed:2026-10-01T23:59:59Z..2026-10-01",
+      "query_id": "recall.name.machine-learning",
+      "range_end": "2026-10-01",
+      "range_start": "2026-10-01T23:59:59Z",
+      "search_limit_reached": true,
+      "status": "incomplete",
+      "total_count": 7791
+    }
+  ],
+  "requests_used": 6,
+  "run_id": "20261017T130557000000Z-152e3feb",
+  "since": "2026-09-24",
+  "started_at": "2026-10-17T13:05:57Z",
+  "until": "2026-10-01"
+}

data/observations/2026/10/17/20261017T130557000000Z-152e3feb.jsonl

@@ -0,0 +1,102 @@
+{"archived":false,"candidate_status":"candidate","created_at":"2015-06-05T18:43:52Z","description":"An object-oriented language for modeling large-scale neural systems, along with an IDE for writing and simulating models.","domains":["general-ml"],"fork":false,"forks":7,"github_id":36949278,"homepage":null,"language":"Java","license":null,"methods":["machine-learning"],"name":"sandialabs/n2a","novelty_signals":["description","github-topics","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T22:11:34Z","query_ids":["recall.name.machine-learning"],"stars":30,"topics":["brain","equations","language","nerl-neuromorphic","neurons","scr-1532","simulator","snl-nerl","snl-neuromorphic","snl-prog-models-runtimes"],"updated_at":"2026-10-01T22:11:39Z","url":"https://github.com/sandialabs/n2a"}
+{"archived":false,"candidate_status":"candidate","created_at":"2015-08-06T13:45:52Z","description":"A list of amazing Newsletters","domains":["general-ml"],"fork":false,"forks":389,"github_id":40307075,"homepage":"https://zudochkin.github.io/awesome-newsletters/","language":null,"license":null,"methods":["machine-learning"],"name":"zudochkin/awesome-newsletters","novelty_signals":["description","github-topics","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T13:40:00Z","query_ids":["recall.name.machine-learning"],"stars":4500,"topics":["awesome","awesome-list","email","email-newsletter","emails","newsletter"],"updated_at":"2026-10-16T09:40:53Z","url":"https://github.com/zudochkin/awesome-newsletters"}
+{"archived":false,"candidate_status":"candidate","created_at":"2015-10-24T19:53:36Z","description":"A list of awesome beginners-friendly projects.","domains":["general-ml"],"fork":false,"forks":8024,"github_id":44882201,"homepage":null,"language":null,"license":null,"methods":["machine-learning"],"name":"MunGell/awesome-for-beginners","novelty_signals":["description","github-topics","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T14:58:51Z","query_ids":["recall.name.machine-learning"],"stars":90355,"topics":["awesome","awesome-list","beginner-project","beginners-friendly","list"],"updated_at":"2026-10-17T12:54:46Z","url":"https://github.com/MunGell/awesome-for-beginners"}
+{"archived":false,"candidate_status":"candidate","created_at":"2016-05-17T14:18:36Z","description":"dzetsaka : classification plugin for Qgis","domains":["general-ml"],"fork":false,"forks":24,"github_id":59029116,"homepage":null,"language":"Python","license":"GPL-3.0","methods":["machine-learning"],"name":"nkarasiak/dzetsaka","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T18:03:12Z","query_ids":["recall.name.machine-learning"],"stars":99,"topics":["ai","algorithm","classification","geomatics","plugin","qgis","rf","svm"],"updated_at":"2026-10-01T12:09:53Z","url":"https://github.com/nkarasiak/dzetsaka"}
+{"archived":false,"candidate_status":"candidate","created_at":"2017-02-03T01:37:01Z","description":"Collective communications library with various primitives for multi-machine training.","domains":["general-ml","machine-learning-systems"],"fork":false,"forks":372,"github_id":80786957,"homepage":"https://pytorch.org/docs/stable/distributed.html","language":"C++","license":"NOASSERTION","methods":["machine-learning"],"name":"pytorch/gloo","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T23:10:45Z","query_ids":["recall.name.machine-learning"],"stars":1459,"topics":["collectives","distributed-training","pytorch"],"updated_at":"2026-10-13T14:29:03Z","url":"https://github.com/pytorch/gloo"}
+{"archived":false,"candidate_status":"candidate","created_at":"2017-02-27T11:12:01Z","description":"Özenle seçilmiş Türkçe kaynaklar listesi En: Curated list of Turkish resources","domains":["general-ml"],"fork":false,"forks":572,"github_id":83301572,"homepage":"https://turkcekaynaklar.com/","language":"Shell","license":"NOASSERTION","methods":["machine-learning"],"name":"fatihacet/turkcekaynaklar-com","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T20:11:06Z","query_ids":["recall.name.machine-learning"],"stars":2521,"topics":["kaynaklar","turkce","turkce-kaynak","turkish"],"updated_at":"2026-10-16T14:04:42Z","url":"https://github.com/fatihacet/turkcekaynaklar-com"}
+{"archived":false,"candidate_status":"candidate","created_at":"2017-03-08T15:29:32Z","description":"Repository for the Broad Institute Proteogenomic Data Analysis Center (PGDAC) established by the NIH Clinical Proteomics Tumor Analysis Consortium (CPTAC)","domains":["general-ml","health-and-biomedicine"],"fork":false,"forks":15,"github_id":84335954,"homepage":null,"language":"WDL","license":"NOASSERTION","methods":["machine-learning"],"name":"broadinstitute/PANOPLY","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-16T17:34:15Z","query_ids":["recall.name.machine-learning"],"stars":39,"topics":[],"updated_at":"2026-10-11T12:28:01Z","url":"https://github.com/broadinstitute/PANOPLY"}
+{"archived":false,"candidate_status":"candidate","created_at":"2017-07-01T19:59:36Z","description":"Heterogeneous Machine Learning Lab Website","domains":["general-ml"],"fork":false,"forks":5,"github_id":95985041,"homepage":"http://hlr.github.io","language":"SCSS","license":null,"methods":["machine-learning"],"name":"HLR/HLR.github.io","novelty_signals":["description","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T00:57:28Z","query_ids":["recall.name.machine-learning"],"stars":1,"topics":[],"updated_at":"2026-10-01T00:57:32Z","url":"https://github.com/HLR/HLR.github.io"}
+{"archived":false,"candidate_status":"candidate","created_at":"2017-07-27T13:32:40Z","description":"Satellite image time series in R","domains":["general-ml","science-and-engineering","time-series-and-forecasting"],"fork":false,"forks":91,"github_id":98539507,"homepage":"https://e-sensing.github.io/sitsbook/","language":"R","license":"GPL-2.0","methods":["machine-learning"],"name":"e-sensing/sits","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-16T20:02:38Z","query_ids":["recall.name.machine-learning"],"stars":549,"topics":["big-earth-data","cbers","earth-observation","eo-datacubes","geospatial","image-time-series","land-cover-classification","landsat","planetary-computer","r-spatial","remote-sensing","rspatial","satellite-image-time-series","satellite-imagery","sentinel-2","stac-api","stac-catalog"],"updated_at":"2026-10-16T07:37:18Z","url":"https://github.com/e-sensing/sits"}
+{"archived":true,"candidate_status":"candidate","created_at":"2017-12-22T13:22:00Z","description":"An automated machine learning tool aimed to facilitate AutoML research.","domains":["general-ml","optimization"],"fork":false,"forks":30,"github_id":115117161,"homepage":"https://openml-labs.github.io/gama/master/","language":"Python","license":"Apache-2.0","methods":["machine-learning"],"name":"amore-labs/gama","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T12:09:33Z","query_ids":["recall.name.machine-learning"],"stars":107,"topics":["automl","hyperparameter-optimization","research-tool"],"updated_at":"2026-10-01T12:27:10Z","url":"https://github.com/amore-labs/gama"}
+{"archived":false,"candidate_status":"candidate","created_at":"2018-01-07T20:52:15Z","description":"UCI Chess Engine","domains":["general-ml"],"fork":false,"forks":13,"github_id":116598223,"homepage":null,"language":"C++","license":"GPL-3.0","methods":["machine-learning","neural-network"],"name":"rosenthj/Winter","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T04:22:57Z","query_ids":["recall.name.machine-learning"],"stars":99,"topics":["ai","chess","chess-ai","chess-engine","deep-learning","machine-learning","neural-network","uci"],"updated_at":"2026-10-10T17:26:19Z","url":"https://github.com/rosenthj/Winter"}
+{"archived":false,"candidate_status":"candidate","created_at":"2018-02-21T16:20:08Z","description":"Deep relational learning through differentiable logic programming.","domains":["general-ml"],"fork":false,"forks":15,"github_id":122360637,"homepage":null,"language":"Java","license":"MIT","methods":["machine-learning"],"name":"GustikS/NeuraLogic","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T11:56:08Z","query_ids":["recall.name.machine-learning"],"stars":122,"topics":["deep-learning","differentiable-programming","logic-programming","machine-learning","relational-learning"],"updated_at":"2026-10-01T11:56:14Z","url":"https://github.com/GustikS/NeuraLogic"}
+{"archived":false,"candidate_status":"candidate","created_at":"2018-03-22T14:02:29Z","description":"evalutils helps users create extensions for grand-challenge.org","domains":["general-ml"],"fork":false,"forks":9,"github_id":126344029,"homepage":"https://grand-challenge.org","language":"Python","license":"MIT","methods":["machine-learning"],"name":"DIAGNijmegen/rse-grand-challenge-metrics","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T12:11:30Z","query_ids":["recall.name.machine-learning"],"stars":23,"topics":["docker","machine-learning","pandas","python36","scikit-learn","simpleitk"],"updated_at":"2026-10-01T12:11:35Z","url":"https://github.com/DIAGNijmegen/rse-grand-challenge-metrics"}
+{"archived":false,"candidate_status":"candidate","created_at":"2018-08-20T14:56:07Z","description":"Slides and resources of the Vienna Deep Learning Meetup","domains":["general-ml"],"fork":false,"forks":14,"github_id":145431963,"homepage":null,"language":"Python","license":null,"methods":["machine-learning"],"name":"vdlm/meetups","novelty_signals":["description","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T17:54:35Z","query_ids":["recall.name.machine-learning"],"stars":128,"topics":[],"updated_at":"2026-10-01T17:54:39Z","url":"https://github.com/vdlm/meetups"}
+{"archived":false,"candidate_status":"candidate","created_at":"2018-09-17T20:14:21Z","description":"Open source, scalable software for the analysis of bioacoustic recordings","domains":["general-ml"],"fork":false,"forks":32,"github_id":149182373,"homepage":"http://opensoundscape.org","language":"Python","license":"MIT","methods":["machine-learning"],"name":"kitzeslab/opensoundscape","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T02:07:35Z","query_ids":["recall.name.machine-learning"],"stars":222,"topics":[],"updated_at":"2026-10-15T19:00:07Z","url":"https://github.com/kitzeslab/opensoundscape"}
+{"archived":false,"candidate_status":"candidate","created_at":"2018-11-22T09:21:49Z","description":"Curated list of Python resources for data science.","domains":["general-ml"],"fork":false,"forks":719,"github_id":158673445,"homepage":null,"language":null,"license":"CC0-1.0","methods":["machine-learning"],"name":"r0f1/datascience","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T14:23:27Z","query_ids":["recall.name.machine-learning"],"stars":4680,"topics":["artificial-intelligence","awesome","awesome-list","bayes","data-analysis","data-mining","data-science","data-visualization","datascience","deep-learning","deeplearning","machine-learning","python","statistics"],"updated_at":"2026-10-15T13:57:45Z","url":"https://github.com/r0f1/datascience"}
+{"archived":false,"candidate_status":"candidate","created_at":"2018-11-29T14:07:19Z","description":"A bunch of the articles and instructions","domains":["general-ml"],"fork":false,"forks":14,"github_id":159675768,"homepage":null,"language":"Jupyter Notebook","license":"MIT","methods":["machine-learning"],"name":"foobar167/articles","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T10:03:12Z","query_ids":["recall.name.machine-learning"],"stars":75,"topics":["anaconda-environment","articles","instructions","machine-learning","python-virtual-environment","technology-sg","ubuntu"],"updated_at":"2026-10-01T10:03:17Z","url":"https://github.com/foobar167/articles"}
+{"archived":false,"candidate_status":"candidate","created_at":"2018-12-17T16:56:09Z","description":"Descriptor computation(chemistry) and (optional) storage for machine learning","domains":["general-ml","science-and-engineering"],"fork":false,"forks":68,"github_id":162162924,"homepage":null,"language":"Python","license":"NOASSERTION","methods":["machine-learning"],"name":"bp-kelley/descriptastorus","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T18:26:38Z","query_ids":["recall.name.machine-learning"],"stars":282,"topics":[],"updated_at":"2026-10-13T17:13:33Z","url":"https://github.com/bp-kelley/descriptastorus"}
+{"archived":false,"candidate_status":"candidate","created_at":"2019-04-19T06:54:55Z","description":"Table with operator formulas and mappings at a glance, as much ML documentation is missing details","domains":["general-ml"],"fork":false,"forks":0,"github_id":182217243,"homepage":null,"language":"HTML","license":null,"methods":["machine-learning"],"name":"fdwr/MachineLearningOperators","novelty_signals":["description","github-topics","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T05:00:12Z","query_ids":["recall.name.machine-learning"],"stars":9,"topics":["onnx"],"updated_at":"2026-10-01T05:00:16Z","url":"https://github.com/fdwr/MachineLearningOperators"}
+{"archived":false,"candidate_status":"candidate","created_at":"2019-06-20T00:59:01Z","description":"High throughput synchronous and asynchronous reinforcement learning","domains":["general-ml","reinforcement-learning"],"fork":false,"forks":155,"github_id":192824415,"homepage":"https://samplefactory.dev","language":"Python","license":"MIT","methods":["machine-learning","reinforcement-learning"],"name":"alex-petrenko/sample-factory","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T08:41:51Z","query_ids":["recall.name.machine-learning"],"stars":1025,"topics":["reinforcement-learning"],"updated_at":"2026-10-16T16:41:02Z","url":"https://github.com/alex-petrenko/sample-factory"}
+{"archived":false,"candidate_status":"candidate","created_at":"2019-09-21T17:42:38Z","description":"This PennyLane plugin allows IonQ simulators/hardware to be used as PennyLane devices.","domains":["general-ml"],"fork":false,"forks":14,"github_id":210028593,"homepage":"https://docs.pennylane.ai/projects/ionq","language":"Python","license":"Apache-2.0","methods":["machine-learning"],"name":"PennyLaneAI/PennyLane-IonQ","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T15:44:50Z","query_ids":["recall.name.machine-learning"],"stars":20,"topics":[],"updated_at":"2026-10-09T08:32:37Z","url":"https://github.com/PennyLaneAI/PennyLane-IonQ"}
+{"archived":false,"candidate_status":"candidate","created_at":"2019-11-25T02:49:35Z","description":"A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations","domains":["general-ml","graph-learning","machine-learning-systems"],"fork":false,"forks":66,"github_id":223848498,"homepage":null,"language":"C++","license":"NOASSERTION","methods":["graph-neural-network","machine-learning","neural-network"],"name":"ChrisCummins/ProGraML","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T17:26:49Z","query_ids":["recall.name.machine-learning"],"stars":333,"topics":["compiler-irs","control-flow","data-flow","graph-neural-networks","graph-representation","llvm","llvm-ir","machine-learning","programming-languages"],"updated_at":"2026-10-02T14:40:48Z","url":"https://github.com/ChrisCummins/ProGraML"}
+{"archived":false,"candidate_status":"candidate","created_at":"2019-12-05T18:10:59Z","description":"Lightweight and easy generation of quasi-Monte Carlo sequences with a ton of different methods on one API for easy parameter exploration in scientific machine learning (SciML)","domains":["general-ml","science-and-engineering"],"fork":false,"forks":27,"github_id":226161761,"homepage":"https://docs.sciml.ai/QuasiMonteCarlo/stable/","language":"Julia","license":"MIT","methods":["machine-learning"],"name":"SciML/QuasiMonteCarlo.jl","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-11T22:36:23Z","query_ids":["recall.name.machine-learning"],"stars":124,"topics":["julia","parameter-estimation","physics-informed-learning","quasi-monte-carlo","scientific-machine-learning","sciml"],"updated_at":"2026-10-01T04:59:41Z","url":"https://github.com/SciML/QuasiMonteCarlo.jl"}
+{"archived":false,"candidate_status":"candidate","created_at":"2020-01-11T09:03:22Z","description":"Kubetools - Curated List of Kubernetes Tools","domains":["general-ml"],"fork":false,"forks":638,"github_id":233204187,"homepage":"https://kubetools.collabnix.com","language":"JavaScript","license":"Apache-2.0","methods":["machine-learning"],"name":"collabnix/kubetools","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T13:37:54Z","query_ids":["recall.name.machine-learning"],"stars":3484,"topics":["grafana","hacktoberfest","hacktoberfest2020","helm","helmcharts","helmpack","iot","jenkins","k8s-cluster","kubernetes","kubernetes-cli","kubernetes-clusters","kubernetes-operational","kubernetes-resource","monitoring","monitoring-tool","prometheus","thanos"],"updated_at":"2026-10-17T13:00:33Z","url":"https://github.com/collabnix/kubetools"}
+{"archived":false,"candidate_status":"candidate","created_at":"2020-03-21T23:55:10Z","description":"Robust, GPU-capable root-finding for nonlinear equations, with broadcasting over abstract array types","domains":["general-ml","science-and-engineering"],"fork":false,"forks":4,"github_id":249081903,"homepage":"https://clima.github.io/RootSolvers.jl/dev/","language":"Julia","license":"Apache-2.0","methods":["machine-learning"],"name":"CliMA/RootSolvers.jl","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T17:05:56Z","query_ids":["recall.name.machine-learning"],"stars":9,"topics":["automatic-differentiation","broadcasting","climate-modeling","cuda","gpu","julia","nonlinear-equations","numerical-methods","root-finding","scientific-computing"],"updated_at":"2026-10-01T17:04:39Z","url":"https://github.com/CliMA/RootSolvers.jl"}
+{"archived":false,"candidate_status":"candidate","created_at":"2020-04-08T20:25:53Z","description":"Beta Machine Learning Toolkit","domains":["general-ml"],"fork":false,"forks":14,"github_id":254192992,"homepage":null,"language":"Julia","license":"MIT","methods":["machine-learning","neural-network","random-forest"],"name":"sylvaticus/BetaML.jl","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T15:25:52Z","query_ids":["recall.name.machine-learning"],"stars":107,"topics":["ai","artificial-intelligence","autoencoder","classification","clustering","data-science","decision-trees","deep-learning","feature-importance","imputation","julia","machine-learning","ml","neural-networks","pca","random-forest","regression"],"updated_at":"2026-10-01T15:25:56Z","url":"https://github.com/sylvaticus/BetaML.jl"}
+{"archived":false,"candidate_status":"candidate","created_at":"2020-08-18T04:11:57Z","description":null,"domains":["general-ml"],"fork":false,"forks":14,"github_id":288351985,"homepage":null,"language":"HTML","license":"MIT","methods":["machine-learning"],"name":"CMU-MultiComp-Lab/mmml-course","novelty_signals":["license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T21:56:34Z","query_ids":["recall.name.machine-learning"],"stars":102,"topics":[],"updated_at":"2026-10-04T14:55:40Z","url":"https://github.com/CMU-MultiComp-Lab/mmml-course"}
+{"archived":false,"candidate_status":"candidate","created_at":"2020-08-19T18:56:52Z","description":null,"domains":["general-ml"],"fork":false,"forks":36,"github_id":288813409,"homepage":null,"language":"C++","license":"Apache-2.0","methods":["machine-learning"],"name":"rapidsai/gputreeshap","novelty_signals":["license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T21:38:22Z","query_ids":["recall.name.machine-learning"],"stars":112,"topics":[],"updated_at":"2026-10-01T21:38:24Z","url":"https://github.com/rapidsai/gputreeshap"}
+{"archived":false,"candidate_status":"candidate","created_at":"2020-09-24T14:28:34Z","description":"Computing representations for atomistic machine learning","domains":["general-ml"],"fork":false,"forks":21,"github_id":298303912,"homepage":"http://docs.metatensor.org/featomic/","language":"Rust","license":"BSD-3-Clause","methods":["machine-learning"],"name":"metatensor/featomic","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T14:11:30Z","query_ids":["recall.name.machine-learning"],"stars":83,"topics":[],"updated_at":"2026-10-03T06:27:13Z","url":"https://github.com/metatensor/featomic"}
+{"archived":false,"candidate_status":"candidate","created_at":"2020-11-24T12:47:36Z","description":"Integrated Machine Learning for Multi-omics Classification and Prediction","domains":["general-ml","health-and-biomedicine"],"fork":false,"forks":11,"github_id":315630081,"homepage":null,"language":"R","license":"NOASSERTION","methods":["machine-learning"],"name":"himelmallick/IntegratedLearner","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T01:48:41Z","query_ids":["recall.name.machine-learning"],"stars":33,"topics":["bayesian","machine-learning","metabolomics","metagenomics","multi-omics","multiple-covariates","repeated-measures"],"updated_at":"2026-10-01T01:44:14Z","url":"https://github.com/himelmallick/IntegratedLearner"}
+{"archived":false,"candidate_status":"candidate","created_at":"2020-12-06T22:57:42Z","description":"PyNeuraLogic lets you use Python to create Differentiable Logic Programs","domains":["general-ml","graph-learning"],"fork":false,"forks":25,"github_id":319149352,"homepage":"https://pyneuralogic.readthedocs.io/","language":"Python","license":"MIT","methods":["graph-neural-network","machine-learning","neural-network"],"name":"LukasZahradnik/PyNeuraLogic","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T09:07:16Z","query_ids":["recall.name.machine-learning"],"stars":313,"topics":["deep-learning","differentiable-programming","geometric-deep-learning","graph-neural-networks","logic-programming","machine-learning","python","pytorch","relational-learning"],"updated_at":"2026-10-01T09:07:20Z","url":"https://github.com/LukasZahradnik/PyNeuraLogic"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-01-02T14:10:09Z","description":"A Docker-based devcontainer for Jupyter Notebook's with a focus on Computer Vision, Machine Learning, Finance, Statistics and Visualization.","domains":["computer-vision","general-ml"],"fork":false,"forks":15,"github_id":326196377,"homepage":"https://jakoch.github.io/jupyter-devbox/","language":"Jupyter Notebook","license":"MIT","methods":["machine-learning"],"name":"jakoch/jupyter-devbox","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-11T08:32:04Z","query_ids":["recall.name.machine-learning"],"stars":23,"topics":["debian","devcontainer","docker","imutils","jupyter-notebook","keras","opencv","pandas","python3","scikit-learn","scipy","seaborn","tensorflow"],"updated_at":"2026-10-01T22:45:23Z","url":"https://github.com/jakoch/jupyter-devbox"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-02-02T10:54:49Z","description":"All about the Backstage community (Meetups, Sessions etc.)","domains":["general-ml"],"fork":false,"forks":41,"github_id":335257589,"homepage":"https://backstage.io","language":"JavaScript","license":null,"methods":["machine-learning"],"name":"backstage/community","novelty_signals":["description","github-topics","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T17:58:55Z","query_ids":["recall.name.machine-learning"],"stars":345,"topics":["backstage"],"updated_at":"2026-10-01T17:58:59Z","url":"https://github.com/backstage/community"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-02-09T10:37:33Z","description":"🏆 A ranked list of awesome machine learning Rust libraries.","domains":["general-ml"],"fork":false,"forks":27,"github_id":337370263,"homepage":null,"language":null,"license":"CC-BY-SA-4.0","methods":["machine-learning"],"name":"e-tornike/best-of-ml-rust","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T16:10:45Z","query_ids":["recall.name.machine-learning"],"stars":522,"topics":[],"updated_at":"2026-10-14T11:54:08Z","url":"https://github.com/e-tornike/best-of-ml-rust"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-03-02T16:04:41Z","description":"for profile","domains":["general-ml"],"fork":false,"forks":17,"github_id":343831980,"homepage":null,"language":"Mustache","license":null,"methods":["machine-learning"],"name":"c17hawke/c17hawke","novelty_signals":["description","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T12:12:58Z","query_ids":["recall.name.machine-learning"],"stars":4,"topics":[],"updated_at":"2026-10-01T12:13:02Z","url":"https://github.com/c17hawke/c17hawke"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-03-23T19:05:44Z","description":"Static web template for academics/research groups","domains":["general-ml"],"fork":false,"forks":450,"github_id":350826959,"homepage":"https://sbryngelson.github.io/academic-website-template/","language":"SCSS","license":"MIT","methods":["machine-learning"],"name":"sbryngelson/academic-website-template","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T17:44:46Z","query_ids":["recall.name.machine-learning"],"stars":385,"topics":["academic-website","github-pages","jekyll","research-website","static-site","template"],"updated_at":"2026-10-17T02:36:14Z","url":"https://github.com/sbryngelson/academic-website-template"}
+{"archived":true,"candidate_status":"candidate","created_at":"2021-04-11T20:46:50Z","description":"End of life; no longer maintained. Final public release: v26.06.01.","domains":["general-ml"],"fork":false,"forks":88,"github_id":356975888,"homepage":"https://docs.nvidia.com/cupynumeric/26.06/","language":"Python","license":"NOASSERTION","methods":["machine-learning"],"name":"nv-legate/cupynumeric","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T01:55:24Z","query_ids":["recall.name.machine-learning"],"stars":982,"topics":[],"updated_at":"2026-10-05T14:07:36Z","url":"https://github.com/nv-legate/cupynumeric"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-04-19T15:20:31Z","description":"A human-made, free/open, beginner-friendly, minimal and human-readable language for the live coding of algorithmic electronic music performances, running in the browser","domains":["general-ml"],"fork":false,"forks":11,"github_id":359505832,"homepage":"https://mercury-playground.cc","language":"JavaScript","license":"GPL-3.0","methods":["machine-learning"],"name":"tmhglnd/mercury-playground","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-07T15:22:21Z","query_ids":["recall.name.machine-learning"],"stars":80,"topics":[],"updated_at":"2026-10-05T00:27:36Z","url":"https://github.com/tmhglnd/mercury-playground"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-05-21T16:16:58Z","description":"Python implementation of scTenifoldNet and scTenifoldKnk workflows.","domains":["general-ml"],"fork":false,"forks":13,"github_id":369591333,"homepage":"https://sctenifoldpy.readthedocs.io/en/latest/","language":"Python","license":"MIT","methods":["machine-learning"],"name":"qwerty239qwe/scTenifoldpy","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T16:24:30Z","query_ids":["recall.name.machine-learning"],"stars":68,"topics":[],"updated_at":"2026-10-17T12:40:42Z","url":"https://github.com/qwerty239qwe/scTenifoldpy"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-07-01T14:47:48Z","description":"Notebooks to upload/download marine footage, connect to a citizen science project, train machine learning models and publish marine biological observations.","domains":["computer-vision","general-ml"],"fork":false,"forks":18,"github_id":382066008,"homepage":null,"language":"Python","license":"GPL-3.0","methods":["machine-learning"],"name":"ocean-data-factory-sweden/kso","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T22:04:37Z","query_ids":["recall.name.machine-learning"],"stars":10,"topics":["citizen-science","deep-learning","marine-protected-areas","object-detection"],"updated_at":"2026-10-01T22:04:43Z","url":"https://github.com/ocean-data-factory-sweden/kso"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-08-06T17:16:48Z","description":"A customizable pipeline for multimodal data extraction from MIMIC-IV!","domains":["general-ml","health-and-biomedicine","multimodal-learning","tabular-and-structured-data"],"fork":false,"forks":116,"github_id":393448808,"homepage":null,"language":"Jupyter Notebook","license":"MIT","methods":["machine-learning"],"name":"healthylaife/MIMIC-IV-Data-Pipeline","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T21:05:23Z","query_ids":["recall.name.machine-learning"],"stars":360,"topics":["clinical-notes","electronic-health-records","medical-imaging","mimic","mimic-iv","multimodal","tabular-data","waveforms"],"updated_at":"2026-10-17T03:18:56Z","url":"https://github.com/healthylaife/MIMIC-IV-Data-Pipeline"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-08-09T03:50:41Z","description":"The AI Compendium, previously called the ML Compendium, curates resources and explanations of machine learning (ML) and deep learning, from a business problem through data, AI, engineering, and product.","domains":["general-ml"],"fork":false,"forks":236,"github_id":394140526,"homepage":"https://www.mlcompendium.com","language":null,"license":null,"methods":["machine-learning"],"name":"orico/www.mlcompendium.com","novelty_signals":["description","github-topics","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T06:15:43Z","query_ids":["recall.name.machine-learning"],"stars":2200,"topics":["algorithms","data-science","deep-learning","full-stack","gitbook","machine-learning","marketing","mlcompendium","probability","product-management","statistics","ux-design","ux-experience","ux-research"],"updated_at":"2026-10-15T12:39:51Z","url":"https://github.com/orico/www.mlcompendium.com"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-09-06T08:35:29Z","description":"PhD/MSc course on Machine Learning Security (Univ. Cagliari)","domains":["general-ml"],"fork":false,"forks":27,"github_id":403546015,"homepage":"https://unica-mlsec.github.io/mlsec/","language":"Jupyter Notebook","license":null,"methods":["machine-learning"],"name":"unica-mlsec/mlsec","novelty_signals":["description","github-topics","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T09:01:15Z","query_ids":["recall.name.machine-learning"],"stars":235,"topics":["adversarial-examples","machine-learning","poisoning-attacks","security"],"updated_at":"2026-10-12T17:42:25Z","url":"https://github.com/unica-mlsec/mlsec"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-11-10T20:12:29Z","description":"🎓 Advice and resources for thriving and surviving graduate school","domains":["general-ml"],"fork":false,"forks":47,"github_id":426762768,"homepage":null,"language":"Makefile","license":"MIT","methods":["machine-learning"],"name":"poloclub/awesome-grad-school","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T22:08:58Z","query_ids":["recall.name.machine-learning"],"stars":494,"topics":["awesome","awesome-list","graduate-school","phd"],"updated_at":"2026-10-16T20:43:17Z","url":"https://github.com/poloclub/awesome-grad-school"}
+{"archived":false,"candidate_status":"candidate","created_at":"2022-02-18T08:00:35Z","description":"Statistical Downscaling for Climate Change Projections with a Graphical User Interface","domains":["general-ml","science-and-engineering"],"fork":false,"forks":16,"github_id":460761774,"homepage":null,"language":"Python","license":"GPL-3.0","methods":["machine-learning"],"name":"ahernanzl/pyClim-SDM","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T10:37:25Z","query_ids":["recall.name.machine-learning"],"stars":36,"topics":[],"updated_at":"2026-10-12T06:27:33Z","url":"https://github.com/ahernanzl/pyClim-SDM"}
+{"archived":false,"candidate_status":"candidate","created_at":"2022-02-19T07:59:13Z","description":"Datasets used in the book Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow","domains":["general-ml"],"fork":false,"forks":94,"github_id":461125164,"homepage":null,"language":null,"license":null,"methods":["machine-learning"],"name":"ageron/data","novelty_signals":["description","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T10:56:58Z","query_ids":["recall.name.machine-learning"],"stars":201,"topics":[],"updated_at":"2026-10-14T14:05:48Z","url":"https://github.com/ageron/data"}
+{"archived":false,"candidate_status":"candidate","created_at":"2022-03-05T16:19:44Z","description":"Material correspondiente a AMq2","domains":["general-ml"],"fork":false,"forks":63,"github_id":466504880,"homepage":null,"language":"Jupyter Notebook","license":null,"methods":["machine-learning"],"name":"FIUBA-Posgrado-Inteligencia-Artificial/aprendizaje_maquina_II","novelty_signals":["description","github-topics","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-04T23:43:42Z","query_ids":["recall.name.machine-learning"],"stars":20,"topics":["airflow","databricks","machine-learning","mlops","python"],"updated_at":"2026-10-01T22:19:56Z","url":"https://github.com/FIUBA-Posgrado-Inteligencia-Artificial/aprendizaje_maquina_II"}
+{"archived":false,"candidate_status":"candidate","created_at":"2022-04-21T17:24:28Z","description":"DeepGNN is a framework for training machine learning models on large scale graph data.","domains":["general-ml"],"fork":false,"forks":36,"github_id":484143363,"homepage":null,"language":"Python","license":"MIT","methods":["machine-learning"],"name":"microsoft/DeepGNN","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T17:56:10Z","query_ids":["recall.name.machine-learning"],"stars":144,"topics":[],"updated_at":"2026-10-09T05:24:14Z","url":"https://github.com/microsoft/DeepGNN"}
+{"archived":false,"candidate_status":"candidate","created_at":"2022-06-11T18:00:51Z","description":null,"domains":["general-ml"],"fork":false,"forks":0,"github_id":502420590,"homepage":null,"language":null,"license":null,"methods":["machine-learning"],"name":"lihkir/MachineLearning","novelty_signals":["query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-16T20:48:13Z","query_ids":["recall.name.machine-learning"],"stars":3,"topics":[],"updated_at":"2026-10-01T20:15:21Z","url":"https://github.com/lihkir/MachineLearning"}
+{"archived":false,"candidate_status":"candidate","created_at":"2022-06-27T07:05:53Z","description":"BrainFlow code that sends your brain's relaxation, focus metrics, and machine learned thought commands to vrchat avatar paramaters via OSC.","domains":["general-ml"],"fork":false,"forks":30,"github_id":507799527,"homepage":"https://linktr.ee/ChilloutCharles","language":"Python","license":"MIT","methods":["machine-learning"],"name":"ChilloutCharles/BrainFlowsIntoVRChat","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T21:50:00Z","query_ids":["recall.name.machine-learning"],"stars":347,"topics":["bci","osc","vr","vrchat"],"updated_at":"2026-10-13T12:47:53Z","url":"https://github.com/ChilloutCharles/BrainFlowsIntoVRChat"}
+{"archived":false,"candidate_status":"candidate","created_at":"2022-08-26T19:36:42Z","description":"GitHub repository for deep learning courses owned and maintained by prof. Jahangiry","domains":["general-ml"],"fork":false,"forks":20,"github_id":529383817,"homepage":null,"language":"Jupyter Notebook","license":null,"methods":["machine-learning"],"name":"PJalgotrader/Deep_Learning-USU","novelty_signals":["description","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T18:33:56Z","query_ids":["recall.name.machine-learning"],"stars":24,"topics":[],"updated_at":"2026-10-01T18:34:01Z","url":"https://github.com/PJalgotrader/Deep_Learning-USU"}
+{"archived":false,"candidate_status":"candidate","created_at":"2022-09-27T08:35:23Z","description":"Earth Observation Training Datasets","domains":["general-ml","science-and-engineering"],"fork":false,"forks":12,"github_id":541983199,"homepage":"https://eotdl.com","language":"Jupyter Notebook","license":"MIT","methods":["machine-learning"],"name":"earthpulse/eotdl","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T10:21:45Z","query_ids":["recall.name.machine-learning"],"stars":59,"topics":[],"updated_at":"2026-10-10T13:16:58Z","url":"https://github.com/earthpulse/eotdl"}
+{"archived":false,"candidate_status":"candidate","created_at":"2022-11-03T19:27:11Z","description":null,"domains":["general-ml","interpretability-and-safety"],"fork":false,"forks":3,"github_id":561478176,"homepage":null,"language":"Python","license":null,"methods":["machine-learning"],"name":"SonghuaHu-UMD/Explainable_AI_Comparison","novelty_signals":["github-topics","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T05:11:40Z","query_ids":["recall.name.machine-learning"],"stars":5,"topics":["explainable-ml","interpretable-machine-learning","model-comparison","tree-based-models"],"updated_at":"2026-10-01T05:11:44Z","url":"https://github.com/SonghuaHu-UMD/Explainable_AI_Comparison"}
+{"archived":false,"candidate_status":"candidate","created_at":"2022-12-09T23:33:42Z","description":"GitHub repository for some ML and DL platforms: Python Crash Course, Google Colab, VScode, PyCaret, Tensorflow, Pytorch, Huggingface","domains":["general-ml"],"fork":false,"forks":16,"github_id":576462116,"homepage":null,"language":"Jupyter Notebook","license":null,"methods":["machine-learning"],"name":"PJalgotrader/platforms-and-tools","novelty_signals":["description","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T18:35:17Z","query_ids":["recall.name.machine-learning"],"stars":24,"topics":[],"updated_at":"2026-10-01T18:35:22Z","url":"https://github.com/PJalgotrader/platforms-and-tools"}
+{"archived":false,"candidate_status":"candidate","created_at":"2023-01-03T21:38:56Z","description":"GitHub repository for deep forecasting courses owned and maintained by prof. Jahangiry","domains":["general-ml","time-series-and-forecasting"],"fork":false,"forks":35,"github_id":584923707,"homepage":null,"language":"Jupyter Notebook","license":null,"methods":["machine-learning"],"name":"PJalgotrader/Deep_forecasting-USU","novelty_signals":["description","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T18:15:51Z","query_ids":["recall.name.machine-learning"],"stars":55,"topics":[],"updated_at":"2026-10-01T18:15:56Z","url":"https://github.com/PJalgotrader/Deep_forecasting-USU"}
+{"archived":false,"candidate_status":"candidate","created_at":"2023-02-01T17:05:09Z","description":"Artificial Intelligence Research for Science (AIRS)","domains":["general-ml"],"fork":false,"forks":96,"github_id":596194595,"homepage":"https://www.air4.science/","language":"Jupyter Notebook","license":"GPL-3.0","methods":["machine-learning"],"name":"divelab/AIRS","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T04:10:11Z","query_ids":["recall.name.machine-learning"],"stars":803,"topics":[],"updated_at":"2026-10-12T13:41:54Z","url":"https://github.com/divelab/AIRS"}
+{"archived":false,"candidate_status":"candidate","created_at":"2023-02-17T03:23:43Z","description":null,"domains":["general-ml"],"fork":false,"forks":12,"github_id":602838126,"homepage":null,"language":"Python","license":"MIT","methods":["machine-learning"],"name":"JangWC/RDS","novelty_signals":["license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T03:45:06Z","query_ids":["recall.name.machine-learning"],"stars":12,"topics":[],"updated_at":"2026-10-01T04:03:51Z","url":"https://github.com/JangWC/RDS"}
+{"archived":false,"candidate_status":"candidate","created_at":"2023-03-21T13:25:52Z","description":"FastAPI Backend for a Conversational Agent using Cohere, (Azure) OpenAI, Langchain & Langgraph and Qdrant as VectorDB","domains":["general-ml"],"fork":false,"forks":44,"github_id":616983144,"homepage":null,"language":"Python","license":"MIT","methods":["machine-learning"],"name":"mfmezger/conversational-agent-langchain","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-15T18:00:00Z","query_ids":["recall.name.machine-learning"],"stars":256,"topics":["ai","cohere","fastapi","gemini","langchain","ollama","openai","qdrant","researchassistant","streamlit","vectordatabase"],"updated_at":"2026-10-11T08:57:24Z","url":"https://github.com/mfmezger/conversational-agent-langchain"}
+{"archived":false,"candidate_status":"candidate","created_at":"2023-05-01T20:19:54Z","description":"Prompts for LLMs","domains":["general-ml","natural-language-processing"],"fork":false,"forks":15,"github_id":635033379,"homepage":null,"language":null,"license":"MIT","methods":["machine-learning"],"name":"voytas75/GPTprompts","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T08:35:38Z","query_ids":["recall.name.machine-learning"],"stars":68,"topics":["gpt","llm","nlp","prompts"],"updated_at":"2026-10-01T08:35:42Z","url":"https://github.com/voytas75/GPTprompts"}
+{"archived":false,"candidate_status":"candidate","created_at":"2023-06-23T15:28:52Z","description":"Official implementation of \"Improving and Evaluating Machine Learning Methods for Forensic Shoeprint Matching\".","domains":["general-ml"],"fork":false,"forks":4,"github_id":657678007,"homepage":"https://solemate.streamlit.app/","language":"Jupyter Notebook","license":"MIT","methods":["machine-learning"],"name":"saatvikkher/SoleMate","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T18:08:06Z","query_ids":["recall.name.machine-learning"],"stars":10,"topics":[],"updated_at":"2026-10-01T18:08:12Z","url":"https://github.com/saatvikkher/SoleMate"}
+{"archived":false,"candidate_status":"candidate","created_at":"2023-06-30T05:57:32Z","description":"Easy to use stem (e.g. instrumental/vocals) separation from CLI or as a python package, using a variety of amazing pre-trained models (primarily from UVR)","domains":["general-ml","speech-and-audio"],"fork":false,"forks":205,"github_id":660487718,"homepage":null,"language":"Python","license":"MIT","methods":["machine-learning"],"name":"nomadkaraoke/python-audio-separator","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T23:59:54Z","query_ids":["recall.name.machine-learning"],"stars":1424,"topics":[],"updated_at":"2026-10-17T10:25:13Z","url":"https://github.com/nomadkaraoke/python-audio-separator"}
+{"archived":false,"candidate_status":"candidate","created_at":"2023-09-16T10:23:02Z","description":null,"domains":["general-ml"],"fork":false,"forks":2,"github_id":692386217,"homepage":null,"language":null,"license":null,"methods":["machine-learning"],"name":"P-Darabi/P-Darabi","novelty_signals":["query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T18:55:05Z","query_ids":["recall.name.machine-learning"],"stars":7,"topics":[],"updated_at":"2026-10-01T18:55:10Z","url":"https://github.com/P-Darabi/P-Darabi"}
+{"archived":false,"candidate_status":"candidate","created_at":"2023-12-23T11:59:53Z","description":"Microservices course content","domains":["general-ml"],"fork":false,"forks":2,"github_id":735026375,"homepage":null,"language":"Jupyter Notebook","license":"MIT","methods":["machine-learning"],"name":"jayurbain/Microservices","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T22:19:48Z","query_ids":["recall.name.machine-learning"],"stars":11,"topics":[],"updated_at":"2026-10-01T22:19:52Z","url":"https://github.com/jayurbain/Microservices"}
+{"archived":false,"candidate_status":"candidate","created_at":"2024-01-21T01:42:47Z","description":"A Julia package for Matrix-Product State (MPS)-based time-series analysis.","domains":["general-ml","time-series-and-forecasting"],"fork":false,"forks":4,"github_id":746081236,"homepage":"https://hugopstackhouse.github.io/MPSTime.jl/","language":"Julia","license":"GPL-3.0","methods":["machine-learning"],"name":"hugopstackhouse/MPSTime.jl","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T02:17:40Z","query_ids":["recall.name.machine-learning"],"stars":25,"topics":["machine-learning","matrix-product-states","physics","quantum-machine-learning","quantum-many-body-physics","tensor-networks","tensor-train","tensors","time-series","time-series-analysis"],"updated_at":"2026-10-01T01:56:55Z","url":"https://github.com/hugopstackhouse/MPSTime.jl"}
+{"archived":false,"candidate_status":"candidate","created_at":"2024-02-13T03:57:15Z","description":"The project serves as a strategic advisory tool, capitalizing on the ZySec series of AI models to amplify the capabilities of security professionals in cyber defense and intelligence.","domains":["cybersecurity","general-ml","natural-language-processing"],"fork":false,"forks":15,"github_id":756663799,"homepage":"https://www.zysec.ai","language":"Python","license":"Apache-2.0","methods":["machine-learning"],"name":"ZySec-AI/project-zysec","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-09T23:46:40Z","query_ids":["recall.name.machine-learning"],"stars":79,"topics":["ai","cybersecurity","gpt","infosec","llm","security"],"updated_at":"2026-10-04T17:27:40Z","url":"https://github.com/ZySec-AI/project-zysec"}
+{"archived":false,"candidate_status":"candidate","created_at":"2024-03-12T10:10:09Z","description":"IDP - Aprendizado de Máquina","domains":["general-ml"],"fork":false,"forks":10,"github_id":770874191,"homepage":null,"language":"Jupyter Notebook","license":"MIT","methods":["machine-learning"],"name":"klaytoncastro/idp-machinelearning","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T11:43:41Z","query_ids":["recall.name.machine-learning"],"stars":8,"topics":[],"updated_at":"2026-10-01T11:43:46Z","url":"https://github.com/klaytoncastro/idp-machinelearning"}
+{"archived":false,"candidate_status":"candidate","created_at":"2024-05-02T06:58:17Z","description":null,"domains":["general-ml"],"fork":false,"forks":117,"github_id":794891092,"homepage":null,"language":"Jupyter Notebook","license":null,"methods":["machine-learning"],"name":"DataBytes-Organisation/DiscountMate_new","novelty_signals":["query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T05:13:42Z","query_ids":["recall.name.machine-learning"],"stars":16,"topics":[],"updated_at":"2026-10-13T09:41:37Z","url":"https://github.com/DataBytes-Organisation/DiscountMate_new"}
+{"archived":false,"candidate_status":"candidate","created_at":"2024-05-24T14:22:23Z","description":"Machine Learning extensions to Grafana Scenes","domains":["general-ml"],"fork":false,"forks":4,"github_id":805415814,"homepage":null,"language":"TypeScript","license":"Apache-2.0","methods":["machine-learning"],"name":"grafana/scenes-ml","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-15T14:08:18Z","query_ids":["recall.name.machine-learning"],"stars":19,"topics":[],"updated_at":"2026-10-02T18:51:48Z","url":"https://github.com/grafana/scenes-ml"}
+{"archived":false,"candidate_status":"candidate","created_at":"2024-06-28T11:15:35Z","description":"some machine learning layers for QCD","domains":["general-ml"],"fork":false,"forks":4,"github_id":821360626,"homepage":null,"language":"Python","license":"GPL-3.0","methods":["machine-learning"],"name":"daknuett/qcd_ml","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T12:23:58Z","query_ids":["recall.name.machine-learning"],"stars":5,"topics":[],"updated_at":"2026-10-08T21:27:34Z","url":"https://github.com/daknuett/qcd_ml"}
+{"archived":false,"candidate_status":"candidate","created_at":"2024-08-24T21:34:41Z","description":"CSci 574 Machine Learning Class Rescourses (lecture notebooks, handouts, data files)","domains":["general-ml"],"fork":false,"forks":5,"github_id":847105532,"homepage":null,"language":"Jupyter Notebook","license":"CC0-1.0","methods":["machine-learning"],"name":"csci574-ml/csci574-ml","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T18:22:11Z","query_ids":["recall.name.machine-learning"],"stars":3,"topics":[],"updated_at":"2026-10-01T18:22:15Z","url":"https://github.com/csci574-ml/csci574-ml"}
+{"archived":false,"candidate_status":"candidate","created_at":"2024-10-07T20:25:01Z","description":"Curriculum for the Python/SQL Document Analysis with AI workshop series at the UCSF Library","domains":["general-ml"],"fork":false,"forks":5,"github_id":869160905,"homepage":"https://ucsf-dsos.github.io/UCSF-DSOS-Python-SQL-Workshops/","language":"Jupyter Notebook","license":"MIT","methods":["machine-learning"],"name":"UCSF-DSOS/UCSF-DSOS-Python-SQL-Workshops","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T22:14:24Z","query_ids":["recall.name.machine-learning"],"stars":8,"topics":[],"updated_at":"2026-10-01T22:14:29Z","url":"https://github.com/UCSF-DSOS/UCSF-DSOS-Python-SQL-Workshops"}
+{"archived":false,"candidate_status":"candidate","created_at":"2024-12-12T16:18:14Z","description":null,"domains":["general-ml","health-and-biomedicine"],"fork":false,"forks":54,"github_id":902469591,"homepage":null,"language":"Jupyter Notebook","license":"MIT","methods":["machine-learning"],"name":"microsoft/healthcareai-examples","novelty_signals":["license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T18:16:20Z","query_ids":["recall.name.machine-learning"],"stars":204,"topics":[],"updated_at":"2026-10-05T01:07:37Z","url":"https://github.com/microsoft/healthcareai-examples"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-01-06T03:01:38Z","description":null,"domains":["general-ml"],"fork":false,"forks":12,"github_id":912610716,"homepage":null,"language":"Python","license":"MIT","methods":["machine-learning"],"name":"JangWC/AWOA","novelty_signals":["license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T03:45:52Z","query_ids":["recall.name.machine-learning"],"stars":12,"topics":[],"updated_at":"2026-10-01T04:04:19Z","url":"https://github.com/JangWC/AWOA"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-01-06T21:52:23Z","description":"ezmsg namespace package for machine learning","domains":["general-ml"],"fork":false,"forks":2,"github_id":913022875,"homepage":null,"language":"Python","license":"MIT","methods":["machine-learning"],"name":"ezmsg-org/ezmsg-learn","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T23:33:23Z","query_ids":["recall.name.machine-learning"],"stars":3,"topics":[],"updated_at":"2026-10-01T23:33:27Z","url":"https://github.com/ezmsg-org/ezmsg-learn"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-02-19T03:41:30Z","description":"🎁 A collection of utilities for LeRobot.","domains":["general-ml","robotics-and-control"],"fork":false,"forks":109,"github_id":935190749,"homepage":null,"language":"Python","license":"MIT","methods":["machine-learning"],"name":"Tavish9/any4lerobot","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T21:06:44Z","query_ids":["recall.name.machine-learning"],"stars":1171,"topics":["agibot","awesome","lerobot","libero","openx","rlds","robocasa","robomind","robotics","utils"],"updated_at":"2026-10-15T09:42:20Z","url":"https://github.com/Tavish9/any4lerobot"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-02-28T20:55:26Z","description":null,"domains":["general-ml"],"fork":false,"forks":12,"github_id":940812675,"homepage":null,"language":"Python","license":"MIT","methods":["machine-learning"],"name":"anoresearch/FADO","novelty_signals":["license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T03:48:07Z","query_ids":["recall.name.machine-learning"],"stars":12,"topics":[],"updated_at":"2026-10-01T04:03:42Z","url":"https://github.com/anoresearch/FADO"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-03-10T02:26:15Z","description":"Automated pipeline for generating, verifying, and preparing high-quality function calling datasets for model fine-tuning. Reduces manual annotation through multi-stage validation and conversion to training formats. Built for Azure ML with permissive license models (Phi3.5 MoE, Phi4 etc).","domains":["general-ml"],"fork":false,"forks":3,"github_id":945715221,"homepage":null,"language":"Python","license":"MIT","methods":["machine-learning"],"name":"Azure-Samples/function-calling-data-synthesizer","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T13:38:43Z","query_ids":["recall.name.machine-learning"],"stars":34,"topics":[],"updated_at":"2026-09-17T07:21:42Z","url":"https://github.com/Azure-Samples/function-calling-data-synthesizer"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-03-11T04:23:06Z","description":null,"domains":["general-ml"],"fork":false,"forks":72,"github_id":946394015,"homepage":null,"language":"Jupyter Notebook","license":null,"methods":["machine-learning"],"name":"DataBytes-Organisation/Intelligent-IoT-Data-Management","novelty_signals":["query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T12:24:50Z","query_ids":["recall.name.machine-learning"],"stars":4,"topics":[],"updated_at":"2026-10-01T12:24:57Z","url":"https://github.com/DataBytes-Organisation/Intelligent-IoT-Data-Management"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-05-08T15:24:38Z","description":"arXiv MCP server for fetching and searching papers.","domains":["general-ml"],"fork":false,"forks":6,"github_id":980112341,"homepage":null,"language":"Python","license":"MIT","methods":["machine-learning"],"name":"Ray0907/arXiv-mcp","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T04:47:38Z","query_ids":["recall.name.machine-learning"],"stars":15,"topics":[],"updated_at":"2026-10-01T04:47:22Z","url":"https://github.com/Ray0907/arXiv-mcp"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-05-15T18:35:58Z","description":null,"domains":["general-ml"],"fork":false,"forks":3,"github_id":984322228,"homepage":null,"language":"Jupyter Notebook","license":null,"methods":["machine-learning"],"name":"DrVogtster/CSCI739-Quantum_Machine_Learning","novelty_signals":["query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T04:25:27Z","query_ids":["recall.name.machine-learning"],"stars":5,"topics":[],"updated_at":"2026-10-07T09:11:36Z","url":"https://github.com/DrVogtster/CSCI739-Quantum_Machine_Learning"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-06-06T02:34:22Z","description":null,"domains":["general-ml"],"fork":false,"forks":2,"github_id":997132663,"homepage":null,"language":"JavaScript","license":"Apache-2.0","methods":["machine-learning"],"name":"LF-Decentralized-Trust-labs/zk-learning-group","novelty_signals":["license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T05:11:57Z","query_ids":["recall.name.machine-learning"],"stars":56,"topics":[],"updated_at":"2026-10-01T05:11:40Z","url":"https://github.com/LF-Decentralized-Trust-labs/zk-learning-group"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-06-06T12:21:57Z","description":"MerLin enables researchers to build, train, and benchmark photonic quantum machine learning models using familiar ML tools.","domains":["general-ml"],"fork":false,"forks":26,"github_id":997374304,"homepage":"https://merlinquantum.ai/","language":"Python","license":"MIT","methods":["machine-learning"],"name":"merlinquantum/merlin","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T09:13:27Z","query_ids":["recall.name.machine-learning"],"stars":37,"topics":["benchmark","deep-learning","machine-learning","merlin","merlin-qml","perceval","photonic-quantum-computing","photonic-quantum-machine-learning","python","pytorch","qml","quantum-computing","quantum-machine-learning"],"updated_at":"2026-10-02T08:45:40Z","url":"https://github.com/merlinquantum/merlin"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-06-13T17:01:07Z","description":"⚛️ ML in fusion industry/science 🍩⚡","domains":["general-ml","science-and-engineering"],"fork":false,"forks":2,"github_id":1001601371,"homepage":null,"language":"TeX","license":null,"methods":["machine-learning","neural-network"],"name":"kharitonov-ivan/awesome-ML-in-plasma-physics","novelty_signals":["description","github-topics","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T06:05:30Z","query_ids":["recall.name.machine-learning"],"stars":44,"topics":["control","equillibrium","fusion","grad-shafranov","mhd","physics-informed-neural-networks","physics-simulation","plasma","plasma-physics","stellarator","tokamak"],"updated_at":"2026-10-14T10:52:59Z","url":"https://github.com/kharitonov-ivan/awesome-ML-in-plasma-physics"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-06-27T10:45:29Z","description":"A curated list of awesome open source libraries to deploy, monitor, version and scale agentic applications and systems","domains":["general-ml"],"fork":false,"forks":33,"github_id":1009568281,"homepage":"https://ethicalml.github.io/awesome-production-agentic-systems/","language":null,"license":"MIT","methods":["machine-learning"],"name":"EthicalML/awesome-production-agentic-systems","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T03:00:09Z","query_ids":["recall.name.machine-learning"],"stars":181,"topics":["agentic-framework","agentic-protocol","genai","generative-ai","generative-artificial-intelligence","prompt-enginering"],"updated_at":"2026-10-15T09:17:06Z","url":"https://github.com/EthicalML/awesome-production-agentic-systems"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-08-05T08:19:00Z","description":"Best Practices for STAC","domains":["general-ml"],"fork":false,"forks":3,"github_id":1032381409,"homepage":null,"language":null,"license":"Apache-2.0","methods":["machine-learning"],"name":"radiantearth/stac-best-practices","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-12T18:26:07Z","query_ids":["recall.name.machine-learning"],"stars":32,"topics":[],"updated_at":"2026-10-06T20:18:37Z","url":"https://github.com/radiantearth/stac-best-practices"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-09-26T07:04:17Z","description":"A DuckDB extension for in-database inference","domains":["general-ml"],"fork":false,"forks":7,"github_id":1064530227,"homepage":null,"language":"Rust","license":"Apache-2.0","methods":["machine-learning"],"name":"CogitatorTech/infera","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T09:44:47Z","query_ids":["recall.name.machine-learning"],"stars":137,"topics":["duckdb","duckdb-extension","inference","machine-learning","onnx","rust"],"updated_at":"2026-10-15T18:02:37Z","url":"https://github.com/CogitatorTech/infera"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-11-04T01:52:12Z","description":"Code and data for “Electric Vehicle Charging Load Forecasting: An Experimental Comparison of Machine Learning Methods” (I. Kyriakopoulos, Y. Theodoridis, 2025).","domains":["general-ml","time-series-and-forecasting"],"fork":false,"forks":2,"github_id":1089178940,"homepage":null,"language":"Python","license":"MIT","methods":["machine-learning"],"name":"IasonKyriakopoulos/electric-vehicle-charging-load-forecasting","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T14:56:44Z","query_ids":["recall.name.machine-learning"],"stars":7,"topics":[],"updated_at":"2026-10-01T14:56:48Z","url":"https://github.com/IasonKyriakopoulos/electric-vehicle-charging-load-forecasting"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-11-10T07:19:51Z","description":"A tool designed to manage annotations for bioacoustics.","domains":["general-ml"],"fork":false,"forks":2,"github_id":1093297038,"homepage":"https://spectrolipi.com","language":"JavaScript","license":"GPL-3.0","methods":["machine-learning"],"name":"nishantnnb/spectrolipi","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T15:54:50Z","query_ids":["recall.name.machine-learning"],"stars":11,"topics":["annotations","bioacoustic-analysis","bioacoustics","labeling-tool","machine-learning","spectrogram","spectrogram-analysis","xeno-canto"],"updated_at":"2026-10-01T15:54:54Z","url":"https://github.com/nishantnnb/spectrolipi"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-12-08T21:43:56Z","description":"This repository showcases all activities, events, workshops, and challenges organized by the IT section during the 2025-2026 academic year.","domains":["general-ml"],"fork":false,"forks":22,"github_id":1112615022,"homepage":null,"language":"Jupyter Notebook","license":null,"methods":["machine-learning"],"name":"MicroClub-USTHB/IT-25-26","novelty_signals":["description","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T11:16:50Z","query_ids":["recall.name.machine-learning"],"stars":46,"topics":[],"updated_at":"2026-10-01T11:16:55Z","url":"https://github.com/MicroClub-USTHB/IT-25-26"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-01-21T22:47:30Z","description":"Códigos e referências usados na Pós de Engenharia de Software com IA Aplicada","domains":["general-ml"],"fork":false,"forks":674,"github_id":1139394927,"homepage":"https://unipds.com.br/org-erick-wendel/?utm_source=github&utm_medium=bio&utm_campaign=bolsa_47&utm_term=&utm_content=perfil_erick","language":"TypeScript","license":"NOASSERTION","methods":["machine-learning"],"name":"unipds-engenharia-de-ia-aplicada/engenharia-de-software-com-ia-aplicada","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T16:14:14Z","query_ids":["recall.name.machine-learning"],"stars":1268,"topics":["ai","javascript","langchain-js","typescript"],"updated_at":"2026-10-17T03:40:58Z","url":"https://github.com/unipds-engenharia-de-ia-aplicada/engenharia-de-software-com-ia-aplicada"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-01-30T13:08:51Z","description":null,"domains":["general-ml"],"fork":false,"forks":10,"github_id":1145974864,"homepage":null,"language":"Jupyter Notebook","license":null,"methods":["machine-learning"],"name":"ommabhishek/FactIQ","novelty_signals":["query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T18:52:54Z","query_ids":["recall.name.machine-learning"],"stars":1,"topics":[],"updated_at":"2026-10-01T18:52:59Z","url":"https://github.com/ommabhishek/FactIQ"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-02-13T13:27:46Z","description":null,"domains":["general-ml"],"fork":false,"forks":145,"github_id":1157137387,"homepage":null,"language":"Python","license":null,"methods":["machine-learning"],"name":"Traqora/astroml","novelty_signals":["query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-12T18:31:34Z","query_ids":["recall.name.machine-learning"],"stars":1,"topics":[],"updated_at":"2026-10-01T14:32:26Z","url":"https://github.com/Traqora/astroml"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-02-20T03:39:43Z","description":"Machine Learning Course for PISH. Practical Assignments in Jupyter Notebook Format.","domains":["general-ml"],"fork":false,"forks":28,"github_id":1162262721,"homepage":null,"language":"Jupyter Notebook","license":"MIT","methods":["machine-learning"],"name":"kubenet/ML_course","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T06:40:11Z","query_ids":["recall.name.machine-learning"],"stars":0,"topics":[],"updated_at":"2026-10-01T06:40:15Z","url":"https://github.com/kubenet/ML_course"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-03-13T19:58:59Z","description":"Open-source course materials for PPG2012H: Applied AI Systems and Governance — University of Toronto, Munk School of Global Affairs & Public Policy","domains":["general-ml"],"fork":false,"forks":7,"github_id":1181148942,"homepage":null,"language":"HTML","license":null,"methods":["machine-learning"],"name":"jaxson/ai-policy-course","novelty_signals":["description","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T14:43:44Z","query_ids":["recall.name.machine-learning"],"stars":41,"topics":[],"updated_at":"2026-10-13T03:00:18Z","url":"https://github.com/jaxson/ai-policy-course"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-06-12T15:52:44Z","description":null,"domains":["general-ml"],"fork":false,"forks":4,"github_id":1267511818,"homepage":null,"language":"Python","license":null,"methods":["machine-learning"],"name":"devlup-labs/CogniOS","novelty_signals":["query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-13T11:37:42Z","query_ids":["recall.name.machine-learning"],"stars":7,"topics":[],"updated_at":"2026-10-01T19:47:33Z","url":"https://github.com/devlup-labs/CogniOS"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-06-14T08:34:46Z","description":null,"domains":["general-ml"],"fork":false,"forks":0,"github_id":1269043237,"homepage":null,"language":"HTML","license":null,"methods":["machine-learning"],"name":"MalikAbdulSalam/Machine_Learning_Course_Digiboost","novelty_signals":["query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T11:17:06Z","query_ids":["recall.name.machine-learning"],"stars":8,"topics":[],"updated_at":"2026-10-17T11:02:04Z","url":"https://github.com/MalikAbdulSalam/Machine_Learning_Course_Digiboost"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-06-19T11:07:08Z","description":"Machine learning research code for causal perception: comparing competing structural causal models (SCMs) via interventional and counterfactual distributions, applied to fair credit decisions. Open source by Santander AI Lab.","domains":["general-ml"],"fork":false,"forks":18,"github_id":1274286443,"homepage":"https://github.com/SantanderAI","language":"Python","license":"Apache-2.0","methods":["causal-inference","machine-learning"],"name":"SantanderAI/causal-perception-implementation","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T04:23:26Z","query_ids":["recall.name.machine-learning"],"stars":42,"topics":["causal-inference","causality","counterfactual","credit-scoring","do-calculus","fairness","machine-learning","python","research","responsible-ai","scikit-learn","structural-causal-model"],"updated_at":"2026-10-15T21:41:24Z","url":"https://github.com/SantanderAI/causal-perception-implementation"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-07-01T14:17:24Z","description":null,"domains":["general-ml"],"fork":false,"forks":8,"github_id":1286179626,"homepage":null,"language":"Jupyter Notebook","license":null,"methods":["machine-learning"],"name":"AkshatGarg2005/car-price-prediction-app","novelty_signals":["query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T18:44:29Z","query_ids":["recall.name.machine-learning"],"stars":0,"topics":[],"updated_at":"2026-10-01T18:44:33Z","url":"https://github.com/AkshatGarg2005/car-price-prediction-app"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-09-03T15:17:40Z","description":"Machine Learning for Earth and Environmental Sciences (UNIL, Fall 2025) Official repository for the Fall 2025 \"Machine Learning for Earth & Environmental Sciences\" course at UNIL. If you are taking this course for credits, please fork this repository and push your completed exercises to this fork.","domains":["general-ml"],"fork":false,"forks":6,"github_id":1356122747,"homepage":null,"language":null,"license":null,"methods":["machine-learning"],"name":"tbeucler/2026_ML_EES","novelty_signals":["description","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T11:26:57Z","query_ids":["recall.name.machine-learning"],"stars":0,"topics":[],"updated_at":"2026-10-01T11:27:02Z","url":"https://github.com/tbeucler/2026_ML_EES"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-09-16T03:11:28Z","description":"Reinforcing Agents with Collective Skills","domains":["general-ml"],"fork":false,"forks":17,"github_id":1372451227,"homepage":null,"language":"Python","license":"Apache-2.0","methods":["machine-learning"],"name":"NVlabs/Skill2Env","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T23:59:35Z","query_ids":["recall.name.machine-learning"],"stars":181,"topics":[],"updated_at":"2026-10-16T22:11:39Z","url":"https://github.com/NVlabs/Skill2Env"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-09-29T19:53:13Z","description":null,"domains":["general-ml"],"fork":false,"forks":0,"github_id":1396506596,"homepage":null,"language":"Jupyter Notebook","license":"MIT","methods":["machine-learning"],"name":"Puskar555/financial-fraud-detection","novelty_signals":["license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T23:59:59Z","query_ids":["recall.name.machine-learning"],"stars":0,"topics":[],"updated_at":"2026-10-02T00:00:03Z","url":"https://github.com/Puskar555/financial-fraud-detection"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-09-30T12:15:37Z","description":"Claude Code PRO — полный курс и гайд на русском: CLAUDE.md, settings, skills, subagents, hooks, MCP, плагины, CI. 8 лабораторных, библиотека промптов и гото��ый starter-kit. Здесь бесплатные курсы  по chatgpt -","domains":["general-ml"],"fork":false,"forks":55,"github_id":1397840198,"homepage":"https://t.me/ai_machinelearning_big_data/10997","language":"Shell","license":"MIT","methods":["machine-learning"],"name":"justxor/claude-code-pro-course","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-10-17T13:05:57Z","pushed_at":"2026-10-01T12:10:20Z","query_ids":["recall.name.machine-learning"],"stars":303,"topics":["ai-agents","ai-coding","anthropic","best-practices","claude","claude-code","claude-code-hooks","claude-code-skills","claude-code-subagents","mcp","prompt-engineering","russian","tutorial"],"updated_at":"2026-10-17T06:15:31Z","url":"https://github.com/justxor/claude-code-pro-course"}