Language: en
Pages: 381
Pages: 381
Summary Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences
Language: en
Pages: 384
Pages: 384
Summary Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences
Language: de
Pages: 310
Pages: 310
Generative Modelle haben sich zu einem der spannendsten Themenbereiche der Künstlichen Intelligenz entwickelt: Mit generativem Deep Learning ist es inzwischen
Language: en
Pages: 470
Pages: 470
Grokking Deep Reinforcement Learning uses engaging exercises to teach you how to build deep learning systems. This book combines annotated Python code with intu
Language: en
Pages: 32
Pages: 32
The application of Deep Reinforcement Learning (DRL) in economics has been an area of active research in recent years. A number of recent works have shown how d
Language: en
Pages: 212
Pages: 212
Leverage the power of reward-based training for your deep learning models with Python Key Features Understand Q-learning algorithms to train neural networks usi
Language: en
Pages: 544
Pages: 544
Get hands-on experience in creating state-of-the-art reinforcement learning agents using TensorFlow and RLlib to solve complex real-world business and industry
Language: en
Pages: 135
Pages: 135
The urgent need for vehicle electrification and improvement in fuel efficiency has gained increasing attention worldwide. Regarding this concern, the solution o
Language: en
Pages: 406
Pages: 406
Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, g
Language: en
Pages: 203
Pages: 203
This book starts by presenting the basics of reinforcement learning using highly intuitive and easy-to-understand examples and applications, and then introduces
