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DC Field | Value | Language |
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dc.contributor.author | Sofien Kaabar | - |
dc.date.accessioned | 2024-11-19T02:39:00Z | - |
dc.date.available | 2024-11-19T02:39:00Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | http://thuvienso.thanglong.edu.vn//handle/TLU/11717 | - |
dc.description.abstract | "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." | vi |
dc.language.iso | vi | vi |
dc.publisher | O'Reilly Media | vi |
dc.subject | Electronic trading of securities | Deep learning (Machine learning) | Python (Langage de programmation) | Giao dịch chứng khoán điện tử | Ngôn ngữ lập trình Python | vi |
dc.title | Deep learning for finance : creating machine and deep learning models for trading in Python | vi |
dc.type | Sách/Book | vi |
Appears in Collections | Tin học |
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