Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audience-from data scientists and engineers to students and researchers. You'll begin by working through some basic examples in TensorFlow before diving deeper into topics such as neural network architectures, TensorBoard visualization, TensorFlow abstraction libraries, and multithreaded input pipelines. Once you finish this book, you'll know how to build and deploy production-ready deep learning systems in TensorFlow.
Get up and running with TensorFlow, rapidly and painlessly
Learn how to use TensorFlow to build deep learning models from the ground up
Train popular deep learning models for computer vision and NLP
Use extensive abstraction libraries to make development easier and faster
Learn how to scale TensorFlow, and use clusters to distribute model training
Deploy TensorFlow in a production setting
Download/Read online eBook Learning TensorFlow for free in format:pdf.epub.doc.txt.mobi.fb2.ios.rtf.java.lit.rb.lrf.DjVu
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| 242 pages
27 Aug 2017
O'Reilly Media, Inc, USA
Sebastopol, United States