Reinforcement Learning for Finance

Name: Reinforcement Learning for Finance
Brand: Springer Nature B.V.
SKU: 9781484288368
Price: 1136 CZK
Availability: InStock

Solve Problems in Finance with CNN and RNN Using the TensorFlow Library

Autor: Ahlawat Samit Ahlawat

Jazyk:

Vazba: Brožovaná

Vydavatel: Springer Nature B.V.

Dostupnost: Skladem u dodavatele

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This book introduces reinforcement learning with mathematical theory and practical examples from qua...

Informace o knize

Autor

Ahlawat Samit Ahlawat

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2022

Stránek

440

EAN

9781484288368

Enbook ID

43407544

Vydavatel

Springer Nature B.V.

Hmotnost

614

Rozměry

156 x 234

Kompletní popis

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, andloss functions.

After completing this book, you will understand reinforcement learning with deep q and generative adversarial networks using the TensorFlow library.

What You Will Learn

Understand the fundamentals of reinforcement learning
Apply reinforcement learning programming techniques to solve quantitative-finance problems
Gain insight into convolutional neural networks and recurrent neural networks
Understand the Markov decision process

Who This Book Is For

Data Scientists, Machine Learning engineers and Python programmers who want to apply reinforcement learning to solve problems.

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