Python Notebooks for MXNet

The outline of python notebooks.


  • MNIST: Recognize handwritten digits with multilayer perceptrons and convolutional neural networks
  • Recognize image objects with pre-trained model on the full Imagenet dataset that containing more than 10M images and over 10K classes
  • Char-LSTM: Generates Obama's speeches with character-level LSTM.
  • Matrix Factorization: Recommend movies to users.

Basic Concepts

  • NDArray: manipulating multi-dimensional array
  • Symbol: symbolic expression for neural networks
  • Module : intermediate-level and high-level interface for neural network training and inference.
  • Loading data : feeding data into training/inference programs
  • Mixed programming: developing training algorithms by using NDArray and Symbol together.

How Tos

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