Téléchargez le livre : Reinforcement Learning for Finance

Reinforcement Learning for Finance

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

Éditeur :

Apress


Paru le : 2022-12-26

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Description


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.
Pages
423 pages
Collection
n.c
Parution
2022-12-26
Marque
Apress
EAN papier
9781484288344
EAN PDF
9781484288351
Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
42
Taille du fichier
18237 Ko
Prix
36,47 €
EAN EPUB
9781484288351
Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
42
Taille du fichier
20173 Ko
Prix
36,47 €

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