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Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python [Paperback] Kaabar, Sofien

Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python [Paperback] Kaabar, Sofien

Deep Learning for Finance: Creating Machine & Deep Learning Models for
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Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python [Paperback] Kaabar, Sofien Paperback - 2024

by Sofien Kaabar

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  • Title Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python [Paperback] Kaabar, Sofien
  • Author Sofien Kaabar
  • Binding Paperback
  • Condition New
  • Pages 359
  • Volumes 1
  • Language ENG
  • Publisher O'Reilly Media
  • Publication date 2024-02-13
  • Bookseller's Inventory # 1098148398_new
  • ISBN 9781098148393 / 1098148398
  • Weight 1.27 lbs (0.58 kg)
  • Dimensions 9.19 x 7 x 0.75 in (23.34 x 17.78 x 1.91 cm)
  • Size 0x0x0
  • Category Computers - General Information
  • Library of Congress subjects Python (Computer program language), Artificial intelligence - Financial
  • Dewey Decimal Code 332.028
  • Quantity available 4

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From the publisher

Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning.

Sofien Kaabar--financial author, trading consultant, and institutional market strategist--introduces deep learning strategies that combine technical and quantitative analyses. By fusing deep learning concepts with technical analysis, this unique book presents outside-the-box ideas in the world of financial trading. This A-Z guide also includes a full introduction to technical analysis, evaluating machine learning algorithms, and algorithm optimization.

  • Understand and create machine learning and deep learning models
  • Explore the details behind reinforcement learning and see how it's used in time series
  • Understand how to interpret performance evaluation metrics
  • Examine technical analysis and learn how it works in financial markets
  • Create technical indicators in Python and combine them with ML models for optimization
  • Evaluate the models' profitability and predictability to understand their limitations and potential

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