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Grokking Deep Learning

4.25  ·  Rating details ·  132 ratings  ·  23 reviews
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 ...more
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.
Frances Buontempo
May 16, 2019 rated it really liked it
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.

Nov 06, 2020 rated it really liked it
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
Dec 24, 2019 rated it it was amazing
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
Antonis Maronikolakis
Jun 28, 2019 rated it it was amazing
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
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.
Sep 06, 2019 rated it it was amazing
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.
Henrik Warne
Jan 02, 2020 rated it liked it
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:
Douglas Cosby
Aug 01, 2019 rated it really liked it
Shelves: unowned
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.
Warren Mcpherson
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.
Dmytro Chaban
Apr 12, 2019 rated it it was amazing  ·  review of another edition
Shelves: ai
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 ...more
Nov 21, 2019 rated it it was amazing
Shelves: unfinished
Excellent book! Best explanation of deep learning I have ever seen! Unfinished because I wish I had some real project to apply/test this knowledge on, but right now reading this book felt a bit too abstract. I will surely come back to it if I decide to get deeper into machine learning.
Łukasz Słonina
Very good first half of the book, introduction to deep learning without using framework, code explained step by step. Second half requires either previous knowledge or studying it in details as it has more theory and bigger code samples (It was my first position on deep learning).
Daniel Gallegos
Sep 05, 2020 rated it really liked it  ·  review of another edition
El libro es interesante, te enseña sobre deep learning y te muestra como construir tu propio framework de deep learning y al final tu estes familiarizado con pytorch.

Es un libro que se recomienda para las personas que estan empezando con deep learning.
Steven Lee
Jan 24, 2020 rated it it was amazing
Hard, but good for understanding what forward and backpropagation actually do
great introduction, relies on concept repetition, slow buildup, and code breaks to reinforce learning for the reader.
Gourav Sengupta
Nov 11, 2019 rated it it was amazing
brings wonderful clarity - just like all the grokking series. But needless to say Andrew has given fantastic insights in a very lucid manner
Aug 12, 2019 rated it really liked it
I read only the first few chapters. It is good as an introductory book highlighting the details of implementing a neural network step by step from scratch
Sep 21, 2020 rated it it was amazing
Excellent book. That too without using a deep learning framework. I would recommend people to start with this book in deep learning space.
Jul 10, 2019 rated it it was amazing
if you want learn just deep learning and learn how to neural networks works its good book
Jan 11, 2020 rated it it was amazing
Sophisticated concepts in a simple language. Great book for beginners!
Siddish Reddy
Dec 04, 2019 rated it it was amazing
Best book to get your hands dirty after doing any introduction course! We will even be implementing a barebone DL framework.
Mar 04, 2020 rated it it was amazing
То с чего мне и надо было учиться. Берем маленькую часть ML и прям с нуля строим объяснение. Практической ценности немного, обучающая - огромна. Нравится.
Mlv Prasad
rated it it was amazing
Sep 28, 2020
Kursad Albayraktaroglu
rated it it was amazing
Sep 18, 2020
rated it it was ok
Aug 07, 2020
rated it really liked it
Feb 04, 2020
Pavel Kvas
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Aug 08, 2020
Michele Biondi
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Oct 22, 2019
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