I am amazed by this book that with my rusty math skills I can read from beginning to end without problem. This 3 book series are the first Deep Learning book I can finish with full understanding. The author basically walk through any mechanism/math using step by step code with minimum data sample.
My next step would be fastai book. That was a great book too, but I stopped in the middle of that book to read this series for two reasons: 1. I want to have solid understanding of all fundamentals of machine learning, 2. fastai hides pytorch detailed, I would like to clearly know which is fastai and what is pytorch.
Also seems the paper book is printed on demand. That will probably make sure user always get the print of latest electronic copy.
I wish I found this series of books a year earlier.
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From the Publisher
Is this book for me?
Daniel wrote this book for beginners in general - not only PyTorch beginners. Every now and then he will spend some time explaining some fundamental concepts which are essential to have a proper understanding of what's going on in the code.
This volume is more demanding than the other two, and you’re going to enjoy it more if you already have a solid understanding of deep learning models.
In this third volume of the series, you’ll be introduced to all things sequence-related: recurrent neural networks and their variations, sequence-to-sequence models, attention, self-attention, and Transformers.
This volume also includes a crash course on natural language processing (NLP), from the basics of word tokenization all the way up to fine-tuning large models (BERT and GPT-2) using the HuggingFace library.
By the time you finish this book, you'll have a thorough understanding of the concepts and tools necessary to start developing, training, and fine-tuning language models using PyTorch.
What's inside
- Recurrent neural networks (RNN, GRU, and LSTM) and 1D convolutions
- Seq2Seq models, attention, self-attention, masks, and positional encoding
- Transformers, layer normalization, and the Vision Transformer (ViT)
- BERT, GPT-2, word embeddings, and the HuggingFace library
- ... and more!
How is this book different?
This book is written as if YOU, the reader, were having a conversation with Daniel, the author: he will ask you questions (and give you answers shortly afterward) and also make some (silly) jokes.
Moreover, this book spells concepts out in plain English, avoiding fancy mathematical notation as much as possible.
It shows you the inner workings of sequence models, in a structured, incremental, and from-first-principles approach.
It builds, step-by-step, not only the models themselves but also your understanding as it shows you both the reasoning behind the code and how to avoid some common pitfalls and errors along the way.
"Hi, I'm Daniel!"
I am a data scientist, developer, teacher, and author of this series of books.
I will tell you, briefly, how this series of books came to be. In 2018, before teaching a class, I tried to find a blog post that would visually explain, in a clear and concise manner, the concepts behind binary cross-entropy so that I could show it to my students. Since I could not find any that fit my purpose, I decided to write one myself. It turned out to be my most popular blog post!
My readers have welcomed the simple, straightforward, and conversational way I explained the topic.
Then, in 2019, I used the same approach for writing another blog post: "Understanding PyTorch with an example: a step-by-step tutorial." Once again, I was amazed by the reaction from the readers! It was their positive feedback that motivated me to write this series of books to help beginners start their journey into deep learning and PyTorch.
I hope you enjoy reading these books as much as I enjoyed writing them!
About the author
Top reviews from the United States
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- Reviewed in the United States on June 22, 2023Format: Kindle
Top reviews from other countries
- Amazon カスタマーReviewed in Japan on September 14, 2022
Greatest PyTorch book for beginner and mid-level
Format: KindleVerified Purchase - Alessio AlexiadisReviewed in the United Kingdom on December 19, 2023
The book is fantastic, but...
Format: PaperbackVerified Purchase - Ali MuhammadReviewed in Canada on June 19, 2023
Easy read unlike many other books
Format: PaperbackVerified Purchase - Rott MatthiasReviewed in Germany on February 13, 2023
Interested in (beside others) understanding Transformers and Attention?
Format: PaperbackVerified Purchase - Sebastian StetsReviewed in Germany on March 31, 2022
Extremely helpful book
Format: PaperbackVerified Purchase
