Summary
In this chapter, we built a recommendation system from scratch using PyTorch. We first learned how to use deep learning to power a recommendation system. We then explored and analyzed the MovieLens dataset. We then defined an EmbeddingNet model using PyTorch and trained and evaluated it on the MovieLens dataset.
Finally, we used the trained EmbeddingNet model to create a movie recommendation system. In the next and final chapter of this book, we will learn more about the Hugging Face ecosystem and how PyTorch users can benefit from different Hugging Face products, components, and libraries.
