/handwritten-digit-classifier

NumPy implementation of a neural network for classifying handwritten digits.

Primary LanguagePythonMIT LicenseMIT

Handwritten Digit Classifier

Deep neural network written in Python with NumPy and trained on the MNIST dataset: http://yann.lecun.com/exdb/mnist/.

Description

  • Architecture: 3 hidden layers with 500, 300, and 100 neurons respectively
  • Activation function: ReLU for hidden layers, softmax for output layer
  • Optimization: Adam optimization algorithm, mini-batch size = 128
  • Regularization: Inverted Dropout (keep_prob = 0.8)
  • Features: Gradient checking

Built With

Authors

  • Matthias Wright

License

This project is licensed under the MIT License - see the LICENSE.md file for details