Learning Deep Reinforcement Learning

We learn by interacting with the environment, and the rewards and punishments we receive determine our future behavior. Deep reinforcement learning brings this natural process into artificial intelligence and involves analyzing results to identify the most effective ways to move... forward. Deep reinforcement learning agents can contribute to the success of marketing campaigns, forecast stock growth, and defeat grandmasters in Go and chess. Let’s learn how to create deep learning systems through engaging exercises accompanied by Python code with detailed comments and clear explanations. You will see how algorithms work and learn how to create your own deep reinforcement learning agents using evaluative feedback.

Author: Мигель Моралес

Printhouse: piter

Series: Programmer's Library

Age restrictions: 16+

Year of publication: 2025

ISBN: 9785446139446

Number of pages: 464

Size: 233x165x24 mm

Cover type: soft

Weight: 720 g

ID: 1508934

We learn by interacting with the environment, and the rewards and punishments we receive determine our future behavior. Deep reinforcement learning brings this natural process into artificial intelligence and involves analyzing results to identify the most effective ways to move forward. Deep reinforcement learning agents can contribute to the success of marketing campaigns, forecast stock growth, and defeat grandmasters in Go and chess. Let’s learn how to create deep learning systems through engaging exercises accompanied by Python code with detailed comments and clear explanations. You will see how algorithms work and learn how to create your own deep reinforcement learning agents using evaluative feedback.

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