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Learning Deep Learning: Theory And Practice Of Neural Networks, Computer Vision, Natural Language Processing, And Transformers Using Tensorflo
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Book Reviews (5)
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perfect for engineers
Derived From Web , Feb 14, 2022
If you are a researcher, you should get Goodfellow's book Deep Learning. You learn all the mathematics and detailed analysis of algorithms. But if you are an engineer who does not plan to write a paper on this field and wants to learn it just for work, get this book. This book cuts directly to the chase and skips all the mambo-jumbo. It is very easy to read and very entertaining. I could not say when I read Goodfellow's book.
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Great book with good mix of theory and codes.
Derived From Web , Feb 10, 2022
This book is great for AI practitioners because it introduces the recent development of deep learning techniques with a good amount of codes. It covers a wide range of applications from vision to MLP and depth is just right without going too deep.
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Great writing. Recommend it!
Derived From Web , Feb 7, 2022
DL's best book is. It is absolutely recommended. The printing is a bit bad, since the ink could be rubbed to be blurry somehow.
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One of the best I've seen so far
Derived From Web , Dec 17, 2021
On a general and more detailed level, I find this text easier to read and understand than almost all, if not all of the more recent texts on Deep Learning. I have not yet gone through it nor tested the examples, but so far so good.
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Highly recommended from novice to experts, teaches to code DL with enough theoretical background.
Derived From Web , Aug 24, 2021
i've done this in the hard way, i.e. First, learn Stanford CS229, then Stanford CS224N and then the version of 2019, available on YouTube, does not teach to code transformers. This book is truly comprehensive learning guide for deep learning, which not only shows theory, but also gets your hands dirty on the code. Truly would recommend for any novice that is new to the field of deep learning.
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