TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning (深度學習的TensorFlow：從線性回歸到強化學習)

Bharath Ramsundar, Reza Bosagh Zadeh

TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

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商品描述

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 speech, analyzing video, and predicting the properties of potential medicines.

TensorFlow for Deep Learning teaches concepts through practical examples and builds understanding of deep learning foundations from the ground up. It’s ideal for practicing developers comfortable with designing software systems, but not necessarily with creating learning systems. This book is also useful for scientists and other professionals who are comfortable with scripting, but not necessarily with designing learning algorithms.

  • Gain in-depth knowledge of the TensorFlow API and primitives.
  • Understand how to train and tune machine learning systems with TensorFlow on large datasets.
  • Learn how to use TensorFlow with convolutional networks, recurrent networks, LSTMs, and reinforcement learning.

商品描述(中文翻譯)

學習如何使用TensorFlow解決具有挑戰性的機器學習問題，TensorFlow是Google的一個革命性的深度學習系統。如果您具備基本的線性代數和微積分背景，這本實用書籍將向您展示如何構建和使用深度學習架構。您將學習如何設計能夠檢測圖像中的物體、理解人類語音、分析視頻和預測潛在藥物性質的系統。

《TensorFlow深度學習》通過實際示例教授概念，從基礎開始建立對深度學習的理解。這本書非常適合熟悉設計軟件系統但不一定熟悉創建學習系統的開發人員使用。對於熟悉腳本編寫但不一定熟悉設計學習算法的科學家和其他專業人士也很有用。

本書內容包括：
- 深入了解TensorFlow API和基本原理。
- 理解如何在大型數據集上使用TensorFlow訓練和調整機器學習系統。
- 學習如何使用TensorFlow進行卷積網絡、循環網絡、LSTM和強化學習。

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