Lesson 1
Machine Learning for Trading
Course
Implement machine learning based strategies to make trading decisions using real-world data.
Implement machine learning based strategies to make trading decisions using real-world data.
Last Updated March 4, 2022
Prerequisites:
No experience required
Course Lessons
Lesson 2
01-01 Reading and plotting stock data
Lesson 3
01-02 Working with multiple stocks
Lesson 4
01-03 The power of NumPy
Lesson 5
01-04 Statistical analysis of time series
Lesson 6
01-05 Incomplete data
Lesson 7
01-06 Histograms and scatter plots
Lesson 8
01-07 Sharpe ratio and other portfolio statistics
Lesson 9
01-08 Optimizers: Building a parameterized model
Lesson 10
01-09 Optimizers: How to optimize a portfolio
Lesson 11
02-01 So you want to be a hedge fund manager?
Lesson 12
02-02 Market Mechanics
Lesson 13
02-03 What is a company worth?
Lesson 14
02-04 The Capital Assets Pricing Model (CAPM)
Lesson 15
02-05 How hedge funds use the CAPM
Lesson 16
02-06 Technical Analysis
Lesson 17
02-07 Dealing with Data
Lesson 18
02-08 Efficient Markets Hypothesis
Lesson 19
02-09 The Fundamental Law of active portfolio management
Lesson 20
02-10 Portfolio optimization and the efficient frontier
Lesson 21
03-01 How Machine Learning is used at a hedge fund
Lesson 22
03-02 Regression
Lesson 23
03-03 Assessing a learning algorithm
Lesson 24
03-04 Ensemble learners, bagging and boosting
Lesson 25
03-05 Reinforcement learning
Lesson 26
03-06 Q-Learning
Lesson 27
03-07 Dyna
Lesson 28
Interview with Tammer Kamel
Taught By The Best
Tucker Balch
Instructor
Arpan Chakraborty
Instructor
Arpan is a computer scientist with a PhD from North Carolina State University. He teaches at Georgia Tech (within the Masters in Computer Science program), and is a coauthor of the book Practical Graph Mining with R.
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