Practical Simulations for Machine Learning: Using Synthetic Data for AI

Simulation and synthesis are core parts of the future of AI and machine learning. Consider: programmers, data...
CHF 87.52
CHF 87.52
SKU: 9781492089926
Product Type: Books
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Author: Paris Buttfield-Addison
Format: Paperback
Language: English
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Practical Simulations for Machine Learning: Using Synthetic Data for AI by Buttfield-Addison, Paris

Practical Simulations for Machine Learning: Using Synthetic Data for AI

CHF 87.52

Practical Simulations for Machine Learning: Using Synthetic Data for AI

CHF 87.52
Author: Paris Buttfield-Addison
Format: Paperback
Language: English

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, concentrating 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 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)
  • Train ML models locally, concurrently, and in the cloud
  • Enable ML tools to work with industry-standard game development tools, using PyTorch, TensorFlow, and the Unity ML-Agents and Web Perception Toolkits


Author: Paris Buttfield-Addison, Mars Buttfield-Addison, Tim Nugent
Publisher: O'Reilly Media
Published: 07/12/2022
Pages: 331
Binding Type: Paperback
Weight: 1.18lbs
Size: 9.19h x 7.00w x 0.91d
ISBN: 9781492089926

About the Author
Buttfield-Addison, Paris: -

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.

Manning, Jon: -

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.

Buttfield-Addison, Mars: -

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.


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