Python Reinforcement Learning

Ravichandiran, Sudharsan, Saito, Sean, Shanmugamani, Rajalingappaa

Python Reinforcement Learning
  • 出版商: Packt Publishing
  • 出版日期: 2019-04-17
  • 售價: $1,650
  • 貴賓價: 9.5 折 $1,568
  • 語言: 英文
  • 頁數: 496
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1838649778
  • ISBN-13: 9781838649777
  • 相關分類: Python、程式語言、Reinforcement、DeepLearning

    • 立即出貨 (庫存=1)

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商品描述

Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. This Learning Path will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms.

The Learning Path starts with an introduction to Reinforcement Learning followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms and concepts, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. As you make your way through the book, you'll work on various datasets including image, text, and video. This example-rich guide will introduce you to deep reinforcement learning algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore technologies such as TensorFlow and OpenAI Gym to implement deep learning reinforcement learning algorithms that also predict stock prices, generate natural language, and even build other neural networks. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many more of the recent advancements in reinforcement learning.

By the end of the Learning Path, you will have all the knowledge and experience needed to implement reinforcement learning and deep reinforcement learning in your projects, and you will be all set to enter the world of artificial intelligence to solve various problems in real-life.

This Learning Path includes content from the following Packt products:

  • Hands-On Reinforcement Learning with Python by Sudharsan Ravichandiran
  • Python Reinforcement Learning Projects by Sean Saito, Yang Wenzhuo, and Rajalingappaa Shanmugamani

商品描述(中文翻譯)

強化學習（Reinforcement Learning，簡稱RL）是人工智慧中最熱門且最有前景的分支。這個學習路徑將幫助您掌握基本的強化學習演算法，以及進階的深度強化學習演算法。

學習路徑以強化學習介紹為開始，接著介紹OpenAI Gym和TensorFlow。您將探索各種強化學習演算法和概念，例如馬可夫決策過程、蒙特卡羅方法和動態規劃，包括價值和策略迭代。隨著您閱讀本書，您將使用各種數據集，包括圖像、文字和視頻。這本範例豐富的指南將介紹您深度強化學習演算法，例如Dueling DQN、DRQN、A3C、PPO和TRPO。您將在多個領域獲得經驗，包括遊戲、圖像處理和物理模擬。您將探索TensorFlow和OpenAI Gym等技術，實現深度學習強化學習演算法，並預測股票價格、生成自然語言，甚至構建其他神經網絡。您還將學習增強想像代理、從人類偏好中學習、DQfD、HER等最新強化學習進展。

通過這個學習路徑，您將獲得實施強化學習和深度強化學習的所有知識和經驗，並準備好進入人工智慧的世界，解決現實生活中的各種問題。

這個學習路徑包含以下Packt出版的內容：

- 《Hands-On Reinforcement Learning with Python》（作者：Sudharsan Ravichandiran）
- 《Python Reinforcement Learning Projects》（作者：Sean Saito、Yang Wenzhuo和Rajalingappaa Shanmugamani）

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