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.
.. toctree:: :maxdepth: 1 basic/ndarray basic/symbol basic/module basic/data
.. toctree:: :maxdepth: 1 python/linear-regression python/mnist python/predict_image vision/large_scale_classification
Want to contribute an MXNet tutorial? To get started, download the tutorial template.