Summary

We began this book with just a curiosity for what DL and PyTorch Lightning are. Anyone new to the Deep Learning or a curious beginner to PyTorch Lightning can get their feet wet by trying simple image recognition models and then continue to raise their game by learning skills such as Transfer Learning (TL) or how to make use of other pre-trained architectures. We continued to leverage the PyTorch Lightning framework for doing not just image recognition models but also Natural Language Processing (NLP) models, time series, and other traditional Machine Learning (ML) challenges. Along the way, we learned about RNN, LSTM, and Transformers.

In the next section of the book, we explored exotic DL models such as Generative Adversarial Networks (GANs), Semi-supervised learning, and Self-Supervised Learning that expand the art of what is possible in the domain of ML and these are not just advanced models but super cool ways to create art and lots of fun to work with. We wrapped...