Practical Reinforcement Learning: Develop self-evolving,...

Main
Computers - Programming
Practical Reinforcement Learning:...

Practical Reinforcement Learning: Develop self-evolving, intelligent agents with OpenAI Gym, Python and Java

Farrukh Akhtar

5.0 / 1.0

Колко ви харесва тази книга?

Какво е качеството на файла?

Изтеглете книгата за оценка на качеството

Какво е качеството на изтеглените файлове?

Категории:

Computers - Programming

Година:

2017

Издателство:

Packt Publishing

Език:

english

Страници:

601

ISBN 10:

1787128725

ISBN 13:

9781787128729

Файл:

PDF, 5.83 MB

IPFS:

,

english, 2017

Четете Онлайн

Преобразуването в се извършва

Преобразуването в е неуспешно

Може да се интересувате от

Jeff Heaton — Introduction to Neural Networks with Java, 2nd Edition

Pratap Dangeti — Statistics for Machine Learning: Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R

Richard M. Reese & Jennifer L. Reese & Bostjan Kaluza & Dr. Uday Kamath & Krishna Choppella — Machine Learning: End-to-End guide for Java developers: Data Analysis, Machine Learning, and Neural Networks simplified

Vincent François-Lavet — An Introduction to Deep Reinforcement Learning

Laura Graesser; Wah Loon Keng — Foundations of Deep Reinforcement Learning: Theory and Practice in Python

Sutton, Richard S., Barto, Andrew G. — Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series)

Parag Kulkarni(auth.) — Reinforcement and Systemic Machine Learning for Decision Making

Joseph P. Bigus, Jennifer Bigus — Constructing intelligent agents with Java: a programmer's guide to smarter applications

David L. Poole; Alan K Mackworth — Artificial Intelligence: Foundations of Computational Agents

H. M. Schwartz — Multi-Agent Machine Learning: A Reinforcement Approach

Arup Kumar Sadhu; Amit Konar — Multi-Agent Coordination: A Reinforcement Learning Approach

Susan El-Shamy — Training Games: Everything You Need to Know About Using Games to Reinforce Learning

Masashi Sugiyama — Statistical Reinforcement Learning: Modern Machine Learning Approaches

Mark Wickham [Mark Wickham] — Practical Java Machine Learning: Projects with Google Cloud Platform and Amazon Web Services

Taweh Beysolow — Applied Reinforcement Learning with Python. With OpenAI Gym, Tensorflow and Keras

Rushdi Shams — Java Data Science Cookbook. Explore the power of MLlib, DL4j, Weka and more

Farrukh Akhtar — Practical Reinforcement Learning

Farrukh Akhtar — Practical Reinforcement Learning

Julian Avila — Scikit-Learn Cookbook: Over 80 Recipes for Machine Learning in Python With Scikit-Learn

Mohit Sewak; Rezaul Karim; Pradeep Pujari — Practical Convolutional Neural Networks: Implement advanced deep learning models using Python

Kuntal Ganguly — Learning generative adversarial networks : next-generation deep learning simplified

Maxim Lapan — Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

Sayon Dutta — Reinforcement Learning With TensorFlow: A Beginner’s Guide to Designing Self-Learning Systems With TensorFlow and OpenAI Gym

Aske Plaat — Learning to Play: Reinforcement Learning and Games

Aske Plaat — Deep Reinforcement Learning

The Wise Old King — Big Bro Talks OpenAI/ChatGPT And The Next Revolution Of Wealth

Dr. Engr. S.M. Farrukh Akhtar — Practical Reinforcement Learning: Develop self-evolving, intelligent agents with OpenAI Gym, Python and Java

Unknown — Book

it-ebooks — Reinforcement Learning An Introduction (Complete Draft)

Michael Lederman Littman — Algorithms for Sequential Decision Making

Richard S. Sutton & Andrew G. Barto & Co-Director Autonomous Learning Laboratory Andrew G Barto & Francis Bach — Reinforcement Learning: An Introduction

Ashwin Rao, Tikhon Jelvis — Foundations of Reinforcement Learning with Applications in Finance

Olivier Sigaud, Olivier Buffet — Markov Decision Processes in Artificial Intelligence

Li, Chong; Qiu, Meikang — Reinforcement learning for cyber-physical systems with cybersecurity case studies

Miguel Morales — Grokking Deep Reinforcement Learning

Giuseppe Ciaburro — Hands-On Reinforcement Learning with R

Sewak, M. — Deep Reinforcement Learning: Frontiers of Artificial Intelligence

LazyProgrammer — Artificial Intelligence: Reinforcement Learning in Python: Complete guide to artificial intelligence and machine learning, prep for deep reinforcement learning

Най-често използвани термини

Свързани списъци с книги