Deep Learning for Finance
Creating Machine & Deep Learning Models for Trading in Python
Falha ao colocar no Carrinho.
Falha ao adicionar à Lista de Desejos.
Falha ao remover da Lista de Desejos
Falha ao adicionar à Biblioteca
Falha ao seguir podcast
Falha ao parar de seguir podcast
Experimente por R$ 0,00
R$ 19,90 /mês
Compre agora por R$ 44,99
Nenhum método de pagamento padrão foi selecionado.
Pedimos desculpas. Não podemos vender este produto com o método de pagamento selecionado
-
Narrado por:
-
Mike Chamberlain
-
De:
-
Sofien Kaabar
Sobre este áudio
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.
PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
©2024 Sofien Kaabar (P)2024 Ascent Audio