×
Dodano do koszyka:
Pozycja znajduje się w koszyku, zwiększono ilość tej pozycji:
Zakupiłeś już tę pozycję:
Książkę możesz pobrać z biblioteki w panelu użytkownika
Pozycja znajduje się w koszyku
Przejdź do koszyka

Zawartość koszyka

ODBIERZ TWÓJ BONUS :: »

TensorFlow 2 Reinforcement Learning Cookbook. Over 50 recipes to help you build, train, and deploy learning agents for real-world applications

(ebook) (audiobook) (audiobook) Książka w języku angielskim
Autor:
Palanisamy P
TensorFlow 2 Reinforcement Learning Cookbook. Over 50 recipes to help you build, train, and deploy learning agents for real-world applications Palanisamy P - okladka książki

TensorFlow 2 Reinforcement Learning Cookbook. Over 50 recipes to help you build, train, and deploy learning agents for real-world applications Palanisamy P - okladka książki

TensorFlow 2 Reinforcement Learning Cookbook. Over 50 recipes to help you build, train, and deploy learning agents for real-world applications Palanisamy P - audiobook MP3

TensorFlow 2 Reinforcement Learning Cookbook. Over 50 recipes to help you build, train, and deploy learning agents for real-world applications Palanisamy P - audiobook CD

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
472
Dostępne formaty:
     PDF
     ePub
     Mobi
With deep reinforcement learning, you can build intelligent agents, products, and services that can go beyond computer vision or perception to perform actions. TensorFlow 2.x is the latest major release of the most popular deep learning framework used to develop and train deep neural networks (DNNs). This book contains easy-to-follow recipes for leveraging TensorFlow 2.x to develop artificial intelligence applications.
Starting with an introduction to the fundamentals of deep reinforcement learning and TensorFlow 2.x, the book covers OpenAI Gym, model-based RL, model-free RL, and how to develop basic agents. You'll discover how to implement advanced deep reinforcement learning algorithms such as actor-critic, deep deterministic policy gradients, deep-Q networks, proximal policy optimization, and deep recurrent Q-networks for training your RL agents. As you advance, you’ll explore the applications of reinforcement learning by building cryptocurrency trading agents, stock/share trading agents, and intelligent agents for automating task completion. Finally, you'll find out how to deploy deep reinforcement learning agents to the cloud and build cross-platform apps using TensorFlow 2.x.
By the end of this TensorFlow book, you'll have gained a solid understanding of deep reinforcement learning algorithms and their implementations from scratch.

Wybrane bestsellery

Packt Publishing - inne książki

Zamknij

Przenieś na półkę

Proszę czekać...
ajax-loader

Zamknij

Wybierz metodę płatności