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Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD
by
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequen
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Paperback, 350 pages
Published
February 4th 2020
by O'Reilly Media
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Start your review of Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD

Sep 07, 2020
Alex Linschoten
rated it
it was amazing
·
review of another edition
Shelves:
coding,
datascience
What an amazing book! What an amazing venture Sylvain and Jeremy have undertaken!
I've done parts of the fast.ai video course in the past. I was very excited that a book version was coming, and in this kindle edition they don't disappoint. For those who prefer written materials to videos, this will be an exciting release.
I haven't finished all the materials in the book, but I've read a good way and while it's a different experience to doing the course online, I have been enjoying it so far. The b ...more
I've done parts of the fast.ai video course in the past. I was very excited that a book version was coming, and in this kindle edition they don't disappoint. For those who prefer written materials to videos, this will be an exciting release.
I haven't finished all the materials in the book, but I've read a good way and while it's a different experience to doing the course online, I have been enjoying it so far. The b ...more

I'm a data scientist. Since most of the data that I traditionally used at work was tabular, I rarely had a need for deep learning. That's starting to change as I work on more NLP projects. I read this book and followed along in the accompanying online course because of the hype surrounding fast.ai. I've become a fan. The content gives the motivated student just enough information to feel empowered to go out and learn more. It's in a sweet spot between breezy tutorials and more serious texts like
...more

Great book for everybody who wants to learn deep learning and who would like to refresh their knowledge. Book has code examples and very good explanations. Suggest to read the book while working on your project, this makes learning more effective as you just don't run the code but have to adapt it to your project. I like the way book focuses on writing readable code. Data science doesn't have to be ad hoc code mess. Besides the book look at their homepage, there is tons of useful material.
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It Is the best book I have ever read. Normally I don't recommend to buy deep learning book, because this area changes so drastically. However this book has a Website where the present Changes are also considered. This books starts with a very High Level programming where in some 5/6 Lines of Code one can achieve SOTA. After that it went deep dive to more Details of those 5/6 lines of Code. After Reading this book you will be capable of understanding each Part of deep learning. Subsequently you w
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I absolutely loved this book. I was skeptical at first since I had gone through many courses, each claiming to be 'the one' so when I came across the fastai courses and Jeremy, I shrugged them off at first. I slowly started watching videos with Jeremy in it and fell in love with his philosophy of democratizing AI and his honest effort to make Deep Learning Accessible to everyone. I finally took the course and used this book as a supplement and I regret nothing.
Just a note: The teaching method us ...more
Just a note: The teaching method us ...more

This is a fantastic book.
If you are trying to get into predictive modeling, this is the best place. It does a really good job of introducing complexity at the appropriate time. Each step doesn't seem like a big leap, and somehow by the end of the book you know way more than most others in the industry.
I highly recommend this book for anyone interested in learning practical machine learning skills. ...more
If you are trying to get into predictive modeling, this is the best place. It does a really good job of introducing complexity at the appropriate time. Each step doesn't seem like a big leap, and somehow by the end of the book you know way more than most others in the industry.
I highly recommend this book for anyone interested in learning practical machine learning skills. ...more

Nov 18, 2020
Ricky
added it
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click here.

I really appreciate the effort that Jeremy and Sylvain have put into making deep learning accessible and interesting to a programmer like me. The book is a joy to read and the authors have found the perfect balance between guiding and challenging the reader. I can't recommend it more highly.
...more

I've read many books on ML and DL but none of them detail, on so many levels, the technical aspects of training deep neural networks like this one. A must read for MLE/DS professionals.
...more

Hands down 🙌. This is the best book and course on deep learning. Don't look anywhere else!
...more

No patience for this. Just go here: https://keras.io/examples/
ModuleNotFoundError Traceback (most recent call last)
in ()
1 #hide
2 get_ipython().system('pip install -Uqq fastbook')
----> 3 import fastbook
4 fastbook.setup_book()
1 frames
/usr/local/lib/python3.6/dist-packages/fastai/vision/all.py in ()
1 from ..basics import *
----> 2 from ..callback.all import *
3 from .augment import *
4 from .core import *
5 from .data import *
ModuleNotFoundError: No module named 'fastai.callback.all'; 'fastai.c ...more
ModuleNotFoundError Traceback (most recent call last)
in ()
1 #hide
2 get_ipython().system('pip install -Uqq fastbook')
----> 3 import fastbook
4 fastbook.setup_book()
1 frames
/usr/local/lib/python3.6/dist-packages/fastai/vision/all.py in ()
1 from ..basics import *
----> 2 from ..callback.all import *
3 from .augment import *
4 from .core import *
5 from .data import *
ModuleNotFoundError: No module named 'fastai.callback.all'; 'fastai.c ...more

Great intro to the modern Deep Learning
I often see people asking for a good place to get started with AI, MachineLearning, and NeuralNets.
This book is a pretty good place. It’s modern (the current version was released in August 2020), centered around the relevant practice, teaches you by doing, going deeper only when needed, and it goes with the course that was updated this August, too. Overall, it’s a great introduction to the field.
I often see people asking for a good place to get started with AI, MachineLearning, and NeuralNets.
This book is a pretty good place. It’s modern (the current version was released in August 2020), centered around the relevant practice, teaches you by doing, going deeper only when needed, and it goes with the course that was updated this August, too. Overall, it’s a great introduction to the field.
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Jeremy Howard is an Australian data scientist and entrepreneur. He began his career in management consulting, at McKinsey & Company and AT Kearney. Howard went on to co-found FastMail in 1999 and Optimal Decisions Group. He later joined Kaggle, an online community for data scientists, as President and Chief Scientist.
Together with Rachel Thomas, he is the co-founder of fast.ai, a research institut ...more
Together with Rachel Thomas, he is the co-founder of fast.ai, a research institut ...more
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Kerine Wint is a software engineering graduate with more love for books than for computers. As an avid reader, writer, and fan of all things...
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