Hope, Tom
Learning tensorflow : A guide to building deep learning systems - 1st - Sebastopol O'Reilly Media, Inc. 2017 - x, 228p. | Binding - Paperback | 23*18 cm
Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics.
Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audiencefrom data scientists and engineers to students and researchers. Youll 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, youll know how to build and deploy production-ready deep learning systems in TensorFlow.
9789352136100
Computer Engineering
006.31 / HOP/RES
Learning tensorflow : A guide to building deep learning systems - 1st - Sebastopol O'Reilly Media, Inc. 2017 - x, 228p. | Binding - Paperback | 23*18 cm
Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics.
Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audiencefrom data scientists and engineers to students and researchers. Youll 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, youll know how to build and deploy production-ready deep learning systems in TensorFlow.
9789352136100
Computer Engineering
006.31 / HOP/RES