Prime Day

Como cliente Amazon Prime obtén 3 meses de Audible gratis
Diseño de la portada del título Deep Learning for Finance

Deep Learning for Finance

Creating Machine & Deep Learning Models for Trading in Python

 Muestra

Escúchalo ahora gratis con tu suscripción a Audible

Prueba gratis durante 30 días
Después de los 30 días, 9,99 €/mes. Cancela tu siguiente plan mensual cuando quieras.
Disfruta de forma ilimitada de este título y de una colección con 90.000 más.
Escucha cuando y donde quieras, incluso sin conexión.
Sin compromiso. Cancela tu siguiente plan mensual cuando quieras.
Más información sobre la suscripción a Audible

Deep Learning for Finance

De: Sofien Kaabar
Narrado por: Mike Chamberlain
Prueba gratis durante 30 días

Después de los 30 días, 9,99 €/mes. Cancela cuando quieras.

Compra ahora por 17,00 €

Compra ahora por 17,00 €

Oferta de tiempo limitado | 0,99 € al mes durante los primeros 3 meses

Obtén este título con una suscripción a Audible Premium: 0,99 € al mes durante los primeros 3 meses
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.



This book will help you to 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; and evaluate the models' profitability and predictability to understand their limitations and potential.©2024 Sofien Kaabar Inversiones y valores
adbl_web_anon_alc_button_suppression_t1
No hay reseñas aún