Tutorial on Recognizing Handwritten Digits with Elixir ML

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Tutorial on Recognizing Handwritten Digits with Elixir ML
Philip Brown demonstrates the power of Elixir for building a machine learning application from scratch. The tutorial serves as an end-to-end guide, starting with setting up the Phoenix framework, preparing the project for machine learning with libraries like Nx and Axon, and processing training data from the MNIST database. Key aspects involve transforming images and labels into a suitable format for the model, defining the model's structure, and training the model with the categorical cross-entropy loss function and accuracy metric. The application provides a LiveView frontend, where users can draw digits, and the system predicts the handwritten numbers using the trained model. Finally, the process includes testing, saving, and loading the model state. Predictions are displayed interactively, leveraging the power of Elixir's live updates without needing external machine learning tools. The full code is available on GitHub.

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