Note, this is an expert edition book - I’d expect professional insights from this book.
As a disclaimer, I’ve been gifted a review copy of this book.
For busy professional like myself, the first 11 chapters gives a good detailed recap of the machine learning world. It’ll be easy for fellow beginners to follow with plenty of diagrams, codes, and clear explainations. Covering almost everything from logistic regression using Scikit-learn, regression analysis, to multilayer artificial neural network.
The next 8 chapters covers the many cool stuffs you can develop with PyTorch, from training GAN networks from scratch, learning OpenAI Gym, sequential modeling, and making real-world predictions.
I’ve learned lots of new stuffs from this book, combining the knowledge of 3 experts. The provided source codes in Jupyter notebooks allows step-by-step learning. It’s available on their GitHub page. Contents and tools are up to date as well.
GitHub source codes: https://github.com/rasbt/machine-learning-book
Available on Amazon: https://amzn.to/3hixms6
