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Practical Simulations for Machine Learning: Using Synthetic Data for AI

MRP: Rs.1,450.00
Price in points: 1450 points
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 1:
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
Leadtime to ship in days (default):
ships in 1-2 days
Leadtime to ship in days(if not in stock):
ships in 12-15 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]