Darowizna 15 września 2024 – 1 października 2024 O zbieraniu funduszy

Practical Reinforcement Learning

Main
Practical Reinforcement Learning

Practical Reinforcement Learning

Farrukh Akhtar

0 / 0

Jak bardzo podobała Ci się ta książka?

Jaka jest jakość pobranego pliku?

Pobierz książkę, aby ocenić jej jakość

Jaka jest jakość pobranych plików?

Rok:

2017

Wydawnictwo:

Packt Publishing

Język:

english

Strony:

270

ISBN 10:

1787127400

ISBN 13:

9781787127401

Plik:

PDF, 6.88 MB

IPFS:

,

english, 2017

Czytaj Online

Trwa konwersja do

Konwersja do nie powiodła się

Możesz być zainteresowany

LazyProgrammer — Unsupervised Deep Learning in Python

Vincent François-Lavet — An Introduction to Deep Reinforcement Learning

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

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

Phil Winder — Reinforcement Learning

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

Schwartz, H. M. [Schwartz, H. M.] — Multi-Agent Machine Learning

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

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

Carl M. Osipov — Cloud Native Machine Learning (MEAP V05)

Bakker, Indra den — Python Deep Learning Cookbook.

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

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

Aske Plaat — Learning to Play: Reinforcement Learning and Games

Kyriakos G. Vamvoudakis (editor), Yan Wan (editor), Frank L. Lewis (editor), Derya Cansever (editor) — Handbook of Reinforcement Learning and Control: 325 (Studies in Systems, Decision and Control, 325)

Todd Hester (auth.) — TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains

王树森　黎彧君　张志华 — 深度强化学习

Najbardziej popularne frazy