Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications

I wish I read this book first. After months of reading, I discovered lablesmoothing, unet, resnet, transformer, etc. This book presents everything in a cohesive work. Other books only do the basics.

Excellent reference to brush on up on project skills. Takes you through all the critical steps with PyTorch and provides online references.

Well layout for easy reading and references.

The code provided in Chapter two is not runnable either due to the dataset issue or out-of-dated code (so I didn’t try to run the rest). Also the book doesn’t cover much more than the tutorials online.

Covers neither Pytorch nor deep learning in depth. Good for beginners.

This book guided me through the maze of machine learning concepts and PyTorch's intricacies. The examples are practical and cover a wide range of topics, from data preprocessing to deploying models. While some advanced topics require a bit of a learning curve, the journey is well worth it.

I actually thought the book was a very good introduction to Pytorch and a good introduction to neural networks at a high level. Although this book is certainly not exhaustive on the latter front, it's not what it set out to do (in other words, don't look at this as a primer on deep learning). My background was heavily focused on TF and Keras. Given the recent advancement of Pytorch, I wanted to see what all the hype was about. The introduction to in the book Pytorch was smooth, slowly introducing newer topics and more difficult topics each chapter. I also like the way the author went from images, to NLP, to speech as IMO, that's probably the ramp up from easiest to hardest topic-wise. He also gives you some additional content on Pytorch in production and some pitfalls that you may experience while using it. Overall, I liked the book and think it gave me a good start to using Pytorch. There's no book that could really prepare you for the intricacies of a language like this; however, the book gives you a solid foundation to stand on.As for the code not working, I would ask the person above to just email the author as he does have the code up on a Github repo. So it may be best to download the latest version.

First initial chapters were good. Code examples from GitHub link worked with only a minor issue or two.Later chapters all down hill - code examples did not work without major issues. It looks like these chapters pulled from posts that the author has made - kind of looks like he just grabbed some stuff and stuck it into a GitHub.Very confusing that the GitHub has a different book title and I don't see the authors name on the site. Started to wonder if the book was a heavy copy and paste.Anyway - loved the first 4 chapters - got lots of useful tricks. NEVER got the code to completely run on any of the following chapters.One of the big issues for me when forking code to my local machines is that the directory references always need some work. When files are completely missing from the chapters I spend a lot of time thinking it's me and a need to fix the directory - really makes me upset to see that the reference file was never included. When authors of books leave out or really make some huge directory assumptions than its clear the book is not very well thought out - books for beginners ?