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Neural Networks from Scratch in Python
"Neural Networks From Scratch" is a book intended to teach you how to build neural networks on your own, without any libraries, so you can better understand deep learning and how all of the elements work. This is so you can go out and do new/novel things with deep learning as well as to become more successful with even more basic models.
This book is to accompany the usual free tutorial videos and sample code from youtube.com/sentdex. This topic is one that warrants multiple mediums and sittings. Having something like a hard copy that you can make notes in, or access without your computer/offline is extremely helpful. All of this plus the ability for backers to highlight and post comments directly in the text should make learning the subject matter even easier.
This book is to accompany the usual free tutorial videos and sample code from youtube.com/sentdex. This topic is one that warrants multiple mediums and sittings. Having something like a hard copy that you can make notes in, or access without your computer/offline is extremely helpful. All of this plus the ability for backers to highlight and post comments directly in the text should make learning the subject matter even easier.
658 pages, Unknown Binding
Published January 1, 2020
59 people are currently reading
397 people want to read
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Displaying 1 - 6 of 6 reviews
September 26, 2023
I think it accomplishes its goal of getting across a deeper understanding of what's happening under the hood of a neural network, by tackling things in raw Python before moving into NumPy.
It never touches PyTorch, TensorFlow, etc, instead giving an arcane intuition for each puzzle piece before you use those libraries later.
Like learning basic car repair before committing to a Sydney to Perth drive. If it goes bad, you potentially won't need to wait for a fixer.
This starts with mapping basic nonlinear functions, then training for prediction on a spiral dataset (shown here), then mapping a sine wave, and finally predicting clothes PNGs using the fashion_mnist dataset. The graphic representations were a big help.
Having not touched vector calculus, the partial derivatives were the most challenging part for me. If there's one thing I'd add to this behemoth, it's some exercises to practice. Though I'm sure I can find those online.
It never touches PyTorch, TensorFlow, etc, instead giving an arcane intuition for each puzzle piece before you use those libraries later.
Like learning basic car repair before committing to a Sydney to Perth drive. If it goes bad, you potentially won't need to wait for a fixer.
This starts with mapping basic nonlinear functions, then training for prediction on a spiral dataset (shown here), then mapping a sine wave, and finally predicting clothes PNGs using the fashion_mnist dataset. The graphic representations were a big help.
Having not touched vector calculus, the partial derivatives were the most challenging part for me. If there's one thing I'd add to this behemoth, it's some exercises to practice. Though I'm sure I can find those online.
February 11, 2021
Learnt so much that I thought I knew but didn't really..
November 22, 2021
Amazing book to understand the concepts behind neural networks. The book is easy to read and examples are really helpful to understand the concepts.
Read
August 5, 2022I wants to learn the concepts of ML
June 18, 2024
Absolutely the best.
November 10, 2022
I enjoyed writing the code from scratch and building on it in every chapter. I will definitely come back to read this every year and see what improvements I can make.
Displaying 1 - 6 of 6 reviews