27-12-2022, 22:08 | view 👀:27 | 🙍 oneddl | redaktor: book24h | Rating👍:

Reinforcement Learning for Finance [#505312]

Name: Reinforcement Learning for Finance
Author: book24h

This book introduces reinforcement learning with mathematical theory and practical examples from quantitative finance using the TensorFlow library.
Reinforcement Learning for Finance begins by describing methods for training neural networks. Next, it discusses CNN and RNN - two kinds of neural networks used as deep learning networks in reinforcement learning. Further, the book dives into reinforcement learning theory, explaining the Markov decision process, value function, policy, and policy gradients, with their mathematical formulations and learning algorithms. It covers recent reinforcement learning algorithms from double deep-Q networks to twin-delayed deep deterministic policy gradients and generative adversarial networks with examples using the TensorFlow Python library. It also serves as a quick hands-on guide to TensorFlow programming, covering concepts ranging from variables and graphs to automatic differentiation, layers, models, and loss functions.

Download From 1DL

rapidgator

https://rapidgator.net/file/3a4b1e27000fc2bc0c01e8409094056d/yq7qm.rar.html

Please Help Me Click Connect Icon Below Here and Share News to Social Network | Thanks you !

⚠️ Dead Link ?
You may submit a re-upload request using the search feature. All requests are reviewed in accordance with our Content Policy.

Request Re-upload

Significant surge in the popularity of free ebook download platforms. These virtual repositories offer an unparalleled range, covering genres that span from classic literature to contemporary non-fiction, and everything in between. Enthusiasts of reading can easily indulge in their passion by accessing free books download online services, which provide instant access to a wealth of knowledge and stories without the physical constraints of space or the financial burden of purchasing hardcover editions.

Reinforcement Learning for Finance [#505312]

Comments (0)

Log in