Description
Hands-On Machine Learning for Algorithmic Trading explores the exciting convergence of data science, artificial intelligence, and financial markets, and is a practical guide to designing automated trading systems. The author shows how machine learning models can be used to uncover hidden patterns in vast amounts of financial data. The book covers the complete process of building a trading system, from data collection to strategy optimization.
In more advanced sections, the concepts of technical analysis, natural language processing for financial news analysis, and price prediction models are taught. Readers learn how to test their strategies in simulated environments to understand how risky they are in the real market. This work is an excellent resource for financial analysts, traders, and data scientists interested in financial markets.
Book Features
- Practical implementation of machine learning and deep learning models in financial markets
- Learning how to collect, clean, and process financial capital market data
- Review of trading strategies based on artificial intelligence and signal analysis
- Teaching backtesting methods to assess the risk and profitability of strategies
- Using the Python programming language and its popular libraries throughout projects
Book specifications
- Publisher: Packt
- Instructor/Author: Stefan Jansen
- Number of pages: 668
- Number of chapters: 21
- Format: PDF
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User Guide
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Download link
File(s) password: www.downloadly.ir
File size
29.5 MB
