Grokking Deep Reinforcement Learning (Paperback)

We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment.

Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

我們都是透過試驗和錯誤學習的。我們避免會帶來痛苦和失敗的事物，並擁抱和建立能給予我們回報和成功的事物。這種常見的模式是深度強化學習的基礎：建立基於環境反應的機器學習系統，進行探索和學習。

《深度強化學習入門》介紹了這種強大的機器學習方法，使用例子、插圖、練習和清晰明瞭的教學。您會喜歡這個完美節奏的教學和巧妙有趣的寫作風格，當您深入探索強化學習基礎、有效的深度學習技術和在這個新興領域的實際應用時。

購買印刷版書籍將包含一本免費的電子書，格式為PDF、Kindle和ePub，由Manning Publications提供。

Miguel Morales is a Senior Software Engineer at Lockheed Martin, Missile and Fire Control-Autonomous Systems. He is also a faculty member at Georgia Institute of Technology where he works as an Instructional Associate for the Reinforcement Learning and Decision Making graduate course. Miguel has worked for numerous other educational and technology companies including Udacity, AT&T, Cisco, and HPE.

Miguel Morales是Lockheed Martin，Missile and Fire Control-Autonomous Systems的高級軟體工程師。他還是喬治亞理工學院的教職成員，擔任強化學習和決策製定研究生課程的教學助理。Miguel曾在許多其他教育和科技公司工作，包括Udacity、AT&T、Cisco和HPE。