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TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning 豆 0.0分
资源最后更新于 2020-11-11 04:13:26
作者：Bharath Ramsundar
出版社：O′Reilly
出版日期：2018-01
ISBN：9781491980453
文件格式： pdf
标签： tensorflow 深度学习 deep-learning 人工智能 软件开发 _...O'Reilly O'Reilly ML/DL
简介· · · · · ·
Learn how to solve challenging machine learning problems with Tensorflow, Google’s revolutionary new system for deep learning. If you have some background with basic linear algebra and calculus, this practical book shows you how to build—and when to use—deep learning architectures. You’ll learn how to design systems capable of detecting objects in images, understanding human sp...
目录
TABLE of CONTENTS
Chapter 1 Introduction to Deep Learning and TensorFlow
Chapter 2 Introduction to TensorFlow Primitives
Chapter 3 Linear Regression with TensorFlow
Chapter 4 Logistic Regression with TensorFlow
Chapter 5 Building a Fully-Connected Deep Network with TensorFlow
Chapter 6 Hyperparameter Optimization
Chapter 7 Convolutional Neural Networks in TensorFlow
Chapter 8 Distributed Training in TensorFlow
Chapter 9 Recurrent Neural Networks with TensorFlow
Chapter 10 Case Study: Reinforcement Learning
Chapter 1 Introduction to Deep Learning and TensorFlow
Chapter 2 Introduction to TensorFlow Primitives
Chapter 3 Linear Regression with TensorFlow
Chapter 4 Logistic Regression with TensorFlow
Chapter 5 Building a Fully-Connected Deep Network with TensorFlow
Chapter 6 Hyperparameter Optimization
Chapter 7 Convolutional Neural Networks in TensorFlow
Chapter 8 Distributed Training in TensorFlow
Chapter 9 Recurrent Neural Networks with TensorFlow
Chapter 10 Case Study: Reinforcement Learning
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