Quick Neural Network Training with Elixir & Axon

Sean Moriarty showcases how Elixir and Axon can be used to train a neural network in a matter of minutes. The example provided uses the MNIST dataset, a classic benchmark in machine learning consisting of handwritten digits. He emphasizes the convenience of using Livebook, which is akin to Jupyter notebooks but for Elixir, to facilitate this process. Moriarty walks through the steps of setting up dependencies, preparing the data for training, creating the neural network model with the Axon API which includes layers such as the dense layer and ReLU activation, and visualizing the model. He then explains the process of converting data into batches, transforming labels into the one-hot encoded format, and finally, running the training loop with Axon, utilizing the EXLA compiler for speeding up the training. The tutorial ends with testing the trained model's accuracy, which impressively reaches 97.1%.