Bộ sách luyện thi ETS 2023 LC&RC
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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
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
Thể loại:Computers - Artificial Intelligence (AI)
Năm:2017
Nhà xuát bản:"O'Reilly Media, Inc."
Ngôn ngữ:english
Trang:242
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