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Grokking Deep Learning
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Artificial Intelligence is one of the most exciting technologies of the century, and Deep Learning is in many ways the “brain” behind some of the world’s smartest Artificial Intelligence systems out there. Loosely based on neuron behavior inside of human brains, these systems are rapidly catching up with the intelligence of their human creators, defeating the world champio
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ebook, 325 pages
Published
2017
by Manning Publications
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A highly interesting and unique book on the subject, which teaches you how to create [deep] neural networks from scratch. In my opinion it could have been been better if it included a little math on the side. Also while the first half of the book holds your hand a lot, the second half picks up the pace way too much.

I like the build-it-yourself approach, rather than showing how to use frameworks.
This helped to build up an understanding.
I did need some previous knowledge of some of the topics - which I personally have - in order to 100% follow, but I know I will revisit this book in the future.
Some parts did take a while to understand, but this is a hard topic.
Well thought through and presented.
This helped to build up an understanding.
I did need some previous knowledge of some of the topics - which I personally have - in order to 100% follow, but I know I will revisit this book in the future.
Some parts did take a while to understand, but this is a hard topic.
Well thought through and presented.

I have yet to find another resource that is able to effectively capture deep learning—without the overuse of frameworks—in a fundamental way. That being said, I did have some experience with DL paradigms before reading this work, so I’m not sure whether or not it was everything that it is meant to be.
1st Chapter - Easy to skim through. I’m really not confident that it is necessary. Could’ve just given a bulleted list of necessary tools in the preface.
2nd Chapter - He does a decent job introducin ...more
1st Chapter - Easy to skim through. I’m really not confident that it is necessary. Could’ve just given a bulleted list of necessary tools in the preface.
2nd Chapter - He does a decent job introducin ...more

A great introductory deep learning book.
Unlike other introductory books that I read (e.g., Deep Learning Illustrated, Deep Learning for Scratch), this book introduces deep learning from ground up -- by implementing key concepts of deep learning from scratch -- and then tying them together into a toy deep learning framework. This helps learn under-the-hood details while appreciating the benefits in a framework. Also, the exposition is limited to a handful of activation functions; hence, the expos ...more
Unlike other introductory books that I read (e.g., Deep Learning Illustrated, Deep Learning for Scratch), this book introduces deep learning from ground up -- by implementing key concepts of deep learning from scratch -- and then tying them together into a toy deep learning framework. This helps learn under-the-hood details while appreciating the benefits in a framework. Also, the exposition is limited to a handful of activation functions; hence, the expos ...more

This was a great read. At first I had qualms about its usefullness, but the more I read the more I liked this. Even though it does not include many mathematics, it is great at tying the maths to a more abstract, high-level understanding.
The way the concepts are described is delightful and intuitive, and the Python code helps in a lot of cases. I did have to skip some parts, as I didn't find much use, but overall it was a great refresher for previous knowledge. Plus, it helped me understand some ...more
The way the concepts are described is delightful and intuitive, and the Python code helps in a lot of cases. I did have to skip some parts, as I didn't find much use, but overall it was a great refresher for previous knowledge. Plus, it helped me understand some ...more

Jun 21, 2019
Beelzefuzz
rated it
really liked it
·
review of another edition
Shelves:
programming,
machine-learning
The only thing I thought could improve this was more examples of how to do something more meaningful with your knowledge. Lots of hard coded vectors until the last 3 or 4 chapters and then the Shakespeare output was not that great. Explains the basic concepts and more difficult ones quite well though. Good beginning for a further exploration with other books.
You build your own PyTorch lite to learn how it works in and out --a pretty cool approach.
You build your own PyTorch lite to learn how it works in and out --a pretty cool approach.

Was hesitating between 4 and 5. In general book is detailed, illustrated with examples and contains the answers to questions that will appear. But tho it's not as easy to grasp as 'Grokking algorithms'. Also, mathematical references are explained ad hoc which is not really convenient for people with some mathematical background -- had to skip a lot. Probably would be awesome to mark those parts as optional.
Giving 5 tho because of the pros. ...more
Giving 5 tho because of the pros. ...more

An introduction to deep learning. Not as good as Grokking Algorithms. Spends too much time on the basics, and covers some quite advanced topics in the end. Also contains numerous small mistakes and oddities. On the plus side, it does give a good understanding of how neural networks work, with many hints on how to think about them.
I have written a more detailed review on my blog: https://henrikwarne.com/2020/01/04/gr... ...more
I have written a more detailed review on my blog: https://henrikwarne.com/2020/01/04/gr... ...more

Definitely recommended. I only really read the first half and skimmed the rest. Well explained introduction to neural networks, with good examples. I checked this out from the library but had to return it before I could actually code any of the examples; however, the code was clear and easy to understand. I will probably shell out the cash to buy this one.

Focusing on the core concepts of deep learning this book runs through examples that get you to start creating core building blocks yourself. Sometimes the best books are not particularly thick but have been edited down so they are focused and manageable. This is easy to get through in a reasonable time and will help most people improve their understanding of deep learning.

That's "Hello, Startup!" in a world of Artificial Intelligence and Deep learning. Book goes through basics. You start by building everything without frameworks so there's no such thing as "what the hell this code is doing" because you see each operation. Although in the middle of the book this started to become burden and I've lost track from time to time, in general everything is pretty clear
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