Practical Simulations for Machine Learning: Using Synthetic Data for AI
暫譯: 機器學習實用模擬：使用合成數據進行AI應用

Buttfield-Addison, Paris, Manning, Jon, Buttfield-Addison, Mars

Practical Simulations for Machine Learning: Using Synthetic Data for AI

相關主題

商品描述

Simulation and synthesis are core parts of the future of AI and machine learning. Consider: programmers, data scientists, and machine learning engineers can create the brain of a self-driving car without the car. Rather than use information from the real world, you can create artificial data using simulations to train traditional machine learning models. That's just the beginning.

With this practical book, you'll explore the possibilities of simulation- and synthesis-based machine learning and AI, with a focus on deep reinforcement learning and imitation learning techniques. AI and ML are increasingly data driven, and simulations are a powerful, engaging way to unlock their full potential.

With this deeply practical book, you'll learn how to:

  • Design an approach for solving ML and AI problems using simulations
  • Use a game engine to synthesize images for use as training data
  • Create simulation environments designed for training deep reinforcement learning and imitation learning
  • Use and apply efficient general-purpose algorithms for simulation-based ML, such as proximal policy optimization (PPO) and soft actor-critic (SAO)
  • Train ML models locally, concurrently, and in the cloud
  • Use PyTorch, TensorFlow, the Unity ML-Agents and Perception Toolkits to enable ML tools to work with industry-standard game development tools

商品描述(中文翻譯)

模擬和合成是未來人工智慧（AI）和機器學習（ML）的核心部分。想想看：程式設計師、資料科學家和機器學習工程師可以創建自駕車的“大腦”而不需要車輛。與其使用來自現實世界的信息，不如利用模擬創建人工數據來訓練傳統的機器學習模型。這僅僅是個開始。

在這本實用的書中，您將探索基於模擬和合成的機器學習和人工智慧的可能性，重點關注深度強化學習和模仿學習技術。AI 和 ML 越來越依賴數據，而模擬則是一種強大且引人入勝的方式，可以釋放它們的全部潛力。

在這本深入實用的書中，您將學習如何：
- 設計一種使用模擬來解決機器學習和人工智慧問題的方法
- 使用遊戲引擎合成圖像作為訓練數據
- 創建專為訓練深度強化學習和模仿學習而設計的模擬環境
- 使用和應用高效的通用算法進行基於模擬的機器學習，例如近端策略優化（PPO）和軟演員-評論家（SAO）
- 在本地、並行和雲端訓練機器學習模型
- 使用 PyTorch、TensorFlow、Unity ML-Agents 和 Perception Toolkits，使機器學習工具能夠與行業標準的遊戲開發工具協同工作

作者簡介

Dr. Paris Buttfield-Addison is cofounder of Secret Lab (https: //www.secretlab.com.au and @TheSecretLab on Twitter), a game development studio based in beautiful Hobart, Australia. Secret Lab builds games and game development tools, including the multi-award winning ABC Play School iPad games, Night in the Woods, the Qantas airlines Joey Playbox games, and the Yarn Spinner narrative game framework. Paris formerly worked as mobile product manager for Meebo (acquired by Google), has a degree in medieval history, a PhD in Computing, and writes technical books on mobile and game development (more than 20 so far) for O'Reilly Media. Paris particularly enjoys game design, statistics, law, machine learning, and human-centred technology research. He can be found on Twitter at @parisba and online at http: //paris.id.au.

Dr. Jon Manning is the cofounder of Secret Lab, an independent game development studio. He's written a whole bunch of books for O'Reilly Media about Swift, iOS development, and game development, and has a doctorate about jerks on the internet. He's currently working on Button Squid, a top-down puzzler, and on the critically acclaimed award winning adventure game Night in the Woods, which includes his interactive dialogue system Yarn Spinner. Jon can be found on Twitter at @desplesda, and online at http: //desplesda.net.

Marina Rose Geldard (Mars) is a technologist from Down Under in Tasmania. Entering the world of technology relatively late as a mature-age student, she has found her place in the world: an industry where she can apply her lifelong love of mathematics and optimization. She compulsively volunteers at industry events, dabbles in research, and serves on the executive committee for her state's branch of the Australian Computer Society (ACS) as well as the AUC. She loves data science, machine learning, and science-fiction. She can be found on Twitter @TheMartianLife and online at https: //themartianlife.com.

Dr. Tim Nugent pretends to be a mobile app developer, game designer, tools builder, researcher, and tech author. When he isn't busy avoiding being found out as a fraud, he spends most of his time designing and creating little apps and games that he won't let anyone see. Tim spent a disproportionately long time writing this tiny little bio, most of which was spent trying to stick a witty sci-fi reference in, before he simply gave up. Tim can be found on Twitter at @The_McJones, and online at http: //lonely.coffee.

作者簡介(中文翻譯)

巴黎·巴特菲爾德-阿迪森博士是Secret Lab的共同創辦人（https://www.secretlab.com.au，Twitter帳號@TheSecretLab），這是一家位於美麗的澳大利亞霍巴特的遊戲開發工作室。Secret Lab開發遊戲和遊戲開發工具，包括多次獲獎的ABC Play School iPad遊戲、《夜晚在樹林中》（Night in the Woods）、澳洲航空的Joey Playbox遊戲，以及Yarn Spinner敘事遊戲框架。巴黎曾擔任Meebo（被Google收購）的行動產品經理，擁有中世紀歷史學位和計算機博士學位，並為O'Reilly Media撰寫了超過20本關於行動和遊戲開發的技術書籍。巴黎特別喜愛遊戲設計、統計學、法律、機器學習和以人為中心的技術研究。他的Twitter帳號是@parisba，網頁是http://paris.id.au。

喬恩·曼寧博士是Secret Lab的共同創辦人，這是一家獨立的遊戲開發工作室。他為O'Reilly Media撰寫了許多關於Swift、iOS開發和遊戲開發的書籍，並擁有關於網路上無禮者的博士學位。他目前正在開發一款名為Button Squid的俯視視角解謎遊戲，以及備受好評的冒險遊戲《夜晚在樹林中》，該遊戲包含他的互動對話系統Yarn Spinner。喬恩的Twitter帳號是@desplesda，網頁是http://desplesda.net。

瑪麗娜·羅斯·蓋爾達德（Mars）是一位來自塔斯馬尼亞的技術專家。作為一名成熟年齡的學生，她相對較晚進入科技領域，卻找到了自己的位置：一個可以應用她對數學和優化的終身熱愛的行業。她在行業活動中自願參加，涉獵研究，並在澳大利亞計算機學會（ACS）及AUC的州分會執行委員會任職。她熱愛數據科學、機器學習和科幻小說。她的Twitter帳號是@TheMartianLife，網頁是https://themartianlife.com。

蒂姆·納根特博士假裝自己是一名行動應用開發者、遊戲設計師、工具開發者、研究人員和技術作者。當他不忙於避免被發現是騙子時，他大部分時間都在設計和創建一些小應用和遊戲，卻不讓任何人看到。蒂姆花了不成比例的長時間來撰寫這段小小的自我介紹，其中大部分時間都在試圖加入一個機智的科幻參考，最後他乾脆放棄了。蒂姆的Twitter帳號是@The_McJones，網頁是http://lonely.coffee。

類似商品