Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python (Paperback)
 
作者: Sofien Kaabar 
分類: Investment & securities ,
3D graphics & modelling ,
Programming & scripting languages: general ,
Machine learning ,
Pattern recognition ,
Computer vision  
書城編號: 27303614

原價: HK$700.00
現售: HK$665 節省: HK$35

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出版社: Oreilly Media
出版日期: 2024/01/23
ISBN: 9781098148393
 
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商品簡介


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
Sofien Kaabar 作者作品表

Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python (Paperback)

eBook: Deep Learning for Finance (DRM EPUB)

eBook: Deep Learning for Finance (DRM PDF)

eBook: Mastering Financial Pattern Recognition (DRM EPUB)

eBook: Mastering Financial Pattern Recognition (DRM PDF)

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