Time Series Forecasting
Keras
English
time-series
stock-forecasting
LSTM
ARIMA
Prophet
machine-learning
deep-learning
forecasting
Instructions to use Hiruni2207/DataSynthis_ML_JobTask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Hiruni2207/DataSynthis_ML_JobTask with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://Hiruni2207/DataSynthis_ML_JobTask") - Notebooks
- Google Colab
- Kaggle
Upload performance_summary.csv with huggingface_hub
Browse files- performance_summary.csv +4 -0
performance_summary.csv
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Model,RMSE,MAPE
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ARIMA,3.3747959050510263,1.89735011501022
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Prophet,4.7650432414652215,3.1859116338570725
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LSTM,2.0890386404819212,1.2515893580288606
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