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Pros & Cons
Pros
The book is written in python and includes code examples to help the reader understand the concepts better. The python source code is online at github and is available for download. The book uses tensorflow 2. Automl, google colab, tpu, tfhub and many... Read More
This is the third edition of this essential volume on deep learning that covers both tensorflow and keras, which is a refreshing change from the norm.
This book is a comprehensive and easy-to-follow guide to artificial intelligence (ai) that is suitable for any learner. The book includes an entire chapter dedicated to mathematics in ai, which is essential for intermediate-level learners. This book p... Read More
The book weighs in at a hefty 699 pages and covers pretty much any topic you want to cover in deep learning. It contains a good, thorough, and understandable explanation of transformers and even the most recent modifications to transformers which take... Read More
Cons
The pages are too wide so you have to lay the book on something or let your arms get exhausted. Got non in the book.
Highlights
Quality
Spam filter machine translation style transfer denoising images convert summer photos to winter using cyclegan play atari game ... Read More
Selforganizing maps som restricted boltzmann machines rbm capsule networks
Nearly 700 pages of indispensable references and examples on how to use two of the most popular and ai and ml libraries out there
We are forced to specialize and thus lose that intuition of the whole
Competitiveness
I had not really used google colab before it was easy and similar to jupyter notebooks
This book also provides a very good introduction to tensor processing unit tpu available from google cloud platform gcp and i... Read More
The next example uses a hugging face model which uses a pretrained model and is much faster and easier to follow
I think that dl has mature enough to stop forcing us to choose between tensorflowkeras or pytorch
Overview
- How are reviewers describing this item?
neural, such, many and model. - Our engine has profiled the reviewer patterns and has determined that there is high deception involved.
- Our engine has analyzed and discovered that 34.3% of the reviews are reliable.
- This product had a total of 78 reviews as of our last analysis date on Apr 30 2024.
Helpful InsightsBETA
Posted by a reviewer on Amazon
The downside though is that the book is littered with typos
Posted by a reviewer on Amazon
Most of the typos have to do with equations or with model results
Posted by a reviewer on Amazon
For example the book incorrectly gives the equation for a plain vanilla lstm and instead gives the equation for a peephole lstm
Posted by a reviewer on Amazon
The typos do not make the book unreadable
Posted by a reviewer on Amazon
But they do require you to double check model equations at every turn to make sure the authors got it right they don’t enough times for it to matter
Posted by a reviewer on Amazon
For a third edition these typos are unexpected and obnoxious
Posted by a reviewer on Amazon
Sample shows color graphs but it’s a black and white print
Posted by a reviewer on Amazon
There are numerous code examples that help readers understand the concepts better and apply them in realworld scenarios
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