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.
- 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.