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Machine Learning Applied to Stock & Crypto Trading – Python

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Machine Learning Applied to Stock Crypto Trading - Python

Machine Learning Applied to Stock & Crypto Trading – Python

Use Unsupervised, Supervised and Reinforcement Learning techniques to gain an edge in trading Stocks, Crypto, Forex.

Created by Shaun McDonogh | 17.5 hours on-demand video course

This course does not cover much in-depth theory. It is purely a hands-on course, with theory at a high level made for anyone to easily grasp the basic concepts, but more importantly, to understand the application and put this to use immediately. If you are looking for a course with a lot of math, this is not the course for you. If you are looking for a course to experience what machine learning is like using financial data in a fun, exciting and potentially profitable way, then you will likely very much enjoy this course.

What you’ll learn

  • Understand hidden states and regimes for any market or asset using Hidden Markov Models
  • Discover optimum assets for pairs trading in ETF’s, Stocks, Forex or Crypto using K-Means Clustering
  • Condense information from a vast array of indicators with PCA
  • Make objective future predictions on financial data with XGBOOST
  • Train an AI Reinforcement Learning agent to trade stocks with PPO
  • Test for market efficiency on any given asset
  • Become familiar with Python Libraries including Pandas, PyTorch (for deep learning) and sklearn

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Josh Smith
Josh Smith

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