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Machine Learning for Finance

Machine Learning techniques for solving major financial issues About This Video Sets a foundation of what to follow by teaching visualization and exploratory analysis of financial data, the typical features like RSI and moving average. Predict stock prices by using Machine Learning models like Linea...

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Detalles Bibliográficos
Autor principal: Singh, Aryan (Autor)
Autor Corporativo: Safari, an O'Reilly Media Company
Formato: Electrónico Video
Idioma:Inglés
Publicado: Packt Publishing, 2020.
Edición:1st edition.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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520 |a Machine Learning techniques for solving major financial issues About This Video Sets a foundation of what to follow by teaching visualization and exploratory analysis of financial data, the typical features like RSI and moving average. Predict stock prices by using Machine Learning models like Linear Regression, Random Forest, XGBoost and neural networks. Use modern portfolio theory, Sharpe ratio, investment simulation, and machine learning to create a rewarding portfolio of stock investments. In Detail Machine Learning for Finance is a perfect course for financial professionals entering the fintech domain. It shows how to solve some of the most common and pressing issues facing institutions in the financial industry, from retail banks to hedge funds. This video course focuses on Machine Learning and covers a range of analysis tools, such as NumPy, Matplotlib, and Pandas. It is packed full of hands-on code simulating many of the problems and providing working solutions. This course aims to build your confidence and the experience to go ahead and tackle real-life problems in financial analysis. The industry is adopting automatic, data-driven algorithms at a rapid pace, and Machine Learning for Finance gives you the skills you need to be at the forefront. By the end of this course, you will be equipped with all the tools from the world of Finance, machine learning and deep learning essential for tackling all these pressing issues in the area of Fintech. 
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