TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning eBook

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Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects in images, understanding text, analyzing video, and predicting the properties of potential medicines. TensorFlow for Deep Learning teaches concepts through practical examples and helps you build knowledge of deep learning foundations from the ground up. It’s ideal for practicing developers with experience designing software systems, and useful for scientists and other professionals familiar with scripting but not necessarily with designing learning algorithms. Learn TensorFlow fundamentals, including how to perform basic computation Build simple learning systems to understand their mathematical foundations Dive into fully connected deep networks used in thousands of applications Turn prototypes into high-quality models with hyperparameter optimization Process images with convolutional neural networks Handle natural language datasets with recurrent neural networks Use reinforcement learning to solve games such as tic-tac-toe Train deep networks with hardware including GPUs and tensor processing units

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Additional ISBNs
9781491980415, 9781491980422

TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning 1st Edition is written by Bharath Ramsundar; Reza Bosagh Zadeh and published by O’Reilly Media. The Digital and eTextbook ISBNs for TensorFlow for Deep Learning are 9781491980408, 1491980400 and the print ISBNs are 9781491980453, 1491980451. Additional ISBNs for this eTextbook include 9781491980415, 9781491980422.