Reinforcement learning : with Open AI, TensorFlow and Keras using Python /: with Open AI, TensorFlow and Keras using Python. ([2018])
- Record Type:
- Book
- Title:
- Reinforcement learning : with Open AI, TensorFlow and Keras using Python /: with Open AI, TensorFlow and Keras using Python. ([2018])
- Main Title:
- Reinforcement learning : with Open AI, TensorFlow and Keras using Python
- Further Information:
- Note: Abhishek Nandy, Manisha Biswas.
- Authors:
- Nandy, Abhishek
Biswas, Manisha - Contents:
- Chapter 1: Reinforcement Learning basics -- Chapter 2: Theory and Algorithms -- Chapter 3: Open AI basics -- Chapter 4: Getting to know Open AI and Open AI Gym the developers way -- Chapter 5: Reinforcement learning using Tensor Flow environment and Keras -- Chapter 6 Google's DeepMind and the future of Reinforcement Learning.
- Publisher Details:
- Berkeley, CA : Apress
- Publication Date:
- 2018
- Copyright Date:
- 2018
- Extent:
- 1 online resource
- Subjects:
- 006.3/1
Computer science
Reinforcement learning
COMPUTERS -- General
Reinforcement learning
Computer Science
Computing Methodologies
Python
Computers -- Programming Languages -- Python
Programming & scripting languages: general
Artificial intelligence
Python (Computer program language)
Computers -- Intelligence (AI) & Semantics
Artificial intelligence
Electronic books
Electronic book - Languages:
- English
- ISBNs:
- 9781484232859
1484232852 - Related ISBNs:
- 9781484232842
1484232844 - Notes:
- Note: Online resource; title from PDF title page (EBSCO, viewed December 20, 2017).
- Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.359987
- Ingest File:
- 01_322.xml