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

Bharath Ramsundar, Reza Bosagh Zadeh

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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,這是 Google 的革命性深度學習系統。如果您對基本的線性代數和微積分有一些背景,這本實用的書籍將向您展示如何構建深度學習架構以及何時使用它們。您將學會設計能夠在圖像中檢測物體、理解人類語音、分析視頻以及預測潛在藥物特性的系統。

《TensorFlow for Deep Learning》通過實際範例教授概念,並從基礎開始建立對深度學習基礎的理解。這本書非常適合那些熟悉設計軟體系統的開發者,但不一定熟悉創建學習系統的人。這本書對於那些熟悉腳本編寫但不一定熟悉設計學習演算法的科學家和其他專業人士也很有幫助。

- 獲得對 TensorFlow API 和基本元件的深入了解。
- 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。
- 學習如何將 TensorFlow 與卷積網絡、遞迴網絡、長短期記憶網絡(LSTMs)和強化學習結合使用。