Tutorials

These tutorials introduce a few fundamental concepts in deep learning and how to implement them in MXNet. The Basics section contains tutorials on manipulating arrays, building networks, loading/preprocessing data, etc. The Training and Inference section talks about implementing Linear Regression, training a Handwritten digit classifier using MLP and CNN, running inferences using a pre-trained model, and lastly, efficiently training a large scale image classifier.

Python

Basics

.. toctree::
   :maxdepth: 1

   basic/ndarray
   basic/symbol
   basic/module
   basic/data

Training and Inference

.. toctree::
   :maxdepth: 1

   python/linear-regression
   python/mnist
   python/predict_image
   vision/large_scale_classification

Contributing Tutorials

Want to contribute an MXNet tutorial? To get started, download the tutorial template.