Practical Simulations for Machine Learning: Using Synthetic Data for AI

Author: Paris Buttfield Addison

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9789355422705
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    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 synthesize 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.

    You'll learn how to:

    • Design an approach for solving ML and AI problems using simulations with the Unity engine
    • Use a game engine to synthesize images for use as training data
    • Create simulation environments designed for training deep reinforcement learning and imitation learning models
    • Use and apply efficient general-purpose algorithms for simulation-based ML, such as proximal policy optimization
    • Train a variety of ML models using different approaches
    • Enable ML tools to work with industry-standard game development tools, using PyTorch, and the Unity ML-Agents and Perception Toolkits
    Books
    Author
    Paris Buttfield Addison
    Author 2
    Mars Buttfield-Addison
    Author 3
    Tim Nugent
    Author 4
    Jon Manning
    Binding
    Paperback
    Condition Type
    New
    Country Origin
    India
    Edition
    First
    Gift Wrap
    N
    Lead time to ship in days (if not in stock)
    ships in 12-15 days
    Leadtime to ship in days (default)
    ships in 1-2 days
    Pages
    336
    Publication Date
    09/06/2022
    Publisher
    Shroff/O'Reilly
    Year
    2022
    Dimensions
    Dimensions (W x H x D)
    7 x 9 x 0.65 inch

    Table of Contents (9789355422705_toc.pdf, 43 Kb) [Download]

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