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Machine-Learning-for-Algorithmic-Trading-Bots-with-Python

This is the code repository for Machine Learning for Algorithmic Trading Bots with Python [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

About the Video Course

Have you ever wondered how the Stock Market, Forex, Cryptocurrency and Online Trading works? Have you ever wanted to become a rich trader having your computers work and make money for you while you’re away for a trip in the Maldives? Ever wanted to land a decent job in a brokerage, bank, or any other prestigious financial institution?We have compiled this course for you in order to seize your moment and land your dream job in financial sector. This course covers the advances in the techniques developed for algorithmic trading and financial analysis based on the recent breakthroughs in machine learning. We leverage the classic techniques widely used and applied by financial data scientists to equip you with the necessary concepts and modern tools to reach a common ground with financial professionals and conquer your next interview.By the end of the course, you will gain a solid understanding of financial terminology and methodology and a hands-on experience in designing and building financial machine learning models. You will be able to evaluate and validate different algorithmic trading strategies. We have a dedicated section to backtesting which is the holy grail of algorithmic trading and is an essential key to successful deployment of reliable algorithms.

The code bundle for this video course is available at - https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-Python

What You Will Learn

  • You will learn about financial terminology and methodology and how to apply them
  • Get hands-on financial data structures and financial machine learning
  • Understand complex financial terminology and methodology in simple ways
  • Ensemble models and cross-validation for financial applications
  • Backtesting for models and strategies evaluation and validation
  • Apply your skills to real world cryptocurrency trading
  • Putting machine learning into real world problems and derive solutions

Instructions and Navigation

Assumed Knowledge

To fully benefit from the coverage included in this course, you will need:
This course is compiled for data science beginners and professionals who want to shift their career to financial sector. This course assumes a basic knowledge of Python programming such as conditional and looping statements. The course is self contained in terms of the concepts, theories, and technologies it requires to build trading bots.

Technical Requirements

This course has the following software requirements:
Eclipse Photon with PyDev Plugin, Latest Version Anaconda platform Google Chrome

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  • Jupyter Notebook 99.9%
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