| --- |
| license: apache-2.0 |
| datasets: |
| - mnist |
| metrics: |
| - accuracy |
| pipeline_tag: image-classification |
| --- |
| |
| # CNN Model for MNIST Digit Classification |
|
|
| This repository contains a Convolutional Neural Network (CNN) model trained on the MNIST dataset for digit classification. The model has achieved an accuracy of 99% on the test dataset and is available for use as a TensorFlow model. |
|
|
| ## Model Details |
| - **Architecture**: Convolutional Neural Network (CNN) |
| - **Input Size**: 28x28 pixels with 1 channel (grayscale) |
| - **Data Preprocessing**: The model has been trained on normalized data. |
| - **Accuracy**: 99% |
|
|
| ## Usage |
| You can use this model for digit classification tasks. Below are some code snippets to help you get started: |
|
|
| ```python |
| # Load the model and perform inference |
| import tensorflow as tf |
| model = tf.keras.models.load_model('model.h5') |
| |
| # Perform inference |
| predictions = model.predict(image) |
| |
| # Get the predicted digit |
| predicted_digit = np.argmax(predictions) |
| |
