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deep learning library Books and Courses

Deep Learning Library books and courses

Book links mentioned below: Tensorflow , Chainer(Not particularly)

Firstly, there are two main libraries for deep learning which are tensorflow and chainer which I consider best for a reason.



Chainer:

Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort.
Chainer supports various network architectures including feed-forward nets, convnets, recurrent nets and recursive nets. It also supports per-batch architectures.
Forward computation can include any control flow statements of Python without lacking the ability of backpropagation. It makes code intuitive and easy to debug.

Best Book for Chainer:




Tensorflow:

TensorFlow, the open source software library developed by the Google Brain team, is a framework for building deep learning neural networks. It is also considered one of the best ways to build deep learning models by machine learning practitioners across the globe. In deep learning models, which rely on a lot of data and computing resources, TensorFlow is used significantly.
Given its flexible architecture for easy deployment on various platforms such as CPUs, GPUs and TPUs, TensorFlow remains one of the favourite libraries to get into ML. Its huge popularity also means that tech enthusiasts are on a constant lookout to learn more and work more with this library.


Best Book for tensorflow: 



If you dont link this book, you can prefer any but I would highly recommend the above book or any other book from the same author: https://amzn.to/2E5sYcu

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