Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Deep Reinforcement Learning with Python: With Pytorch, Tensorflow and OpenAI Gym

Deep Reinforcement Learning with Python: With Pytorch, Tensorflow and OpenAI Gym

Sanghi, Nimish

Paperback

General ComputersProgramming

Currently unavailable to order

ISBN10: 1484268083
ISBN13: 9781484268087
Publisher: Apress
Published: Apr 2 2021
Pages: 382
Weight: 1.54
Height: 0.83 Width: 7.00 Depth: 10.00
Language: English
Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding exercise.
You'll begin by reviewing the Markov decision processes, Bellman equations, and dynamic programming that form the core concepts and foundation of deep reinforcement learning. Next, you'll study model-free learning followed by function approximation using neural networks and deep learning. This is followed by various deep reinforcement learning algorithms such as deep q-networks, various flavors of actor-critic methods, and other policy-based methods.

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