Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python by Sofien Kaabar is a comprehensive resource that delves into the application of deep learning techniques in financial trading. This edition emphasizes practical strategies for developing and backtesting trading algorithms using machine learning, deep learning, and reinforcement learning models.
 
By integrating robust research, evidence-based practices, and compelling narratives, the text fosters a deeper understanding of topics such as technical analysis, time series prediction, and algorithm optimization. It is an invaluable resource for finance professionals, data scientists, and quantitative traders seeking to enhance their knowledge in financial trading and machine learning.
 
Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python by Sofien Kaabar, published by O'Reilly Media in 2024, is available in interactive PDF format, with Print ISBN: 9781098148393 and eTextbook ISBN: 9781098148386. This first edition is categorized under Computers/Data Science/Machine Learning, making it an invaluable asset for those aiming to excel in applying deep learning to financial trading. Purchase this eBook and save up to 80% at ScholarStash.
 
About the Author:
 
Sofien Kaabar: Sofien Kaabar is a financial author, trading consultant, and institutional market strategist specializing in the currencies market with a focus on technical and quantitative topics. He aims to make technical analysis objective by incorporating clear conditions that can be analyzed and created with the use of technical indicators that rival existing ones. Having developed many successful trading algorithms, Sofien is now sharing the knowledge he has acquired over the years to make it accessible to everyone.