This module is your first introduction to machine learning and finance.
You won’t become an expert in machine learning and finance overnight, this course would be highly exploratory, and my hope is to expose you to a board range of pertinent topics, as a result you are expected to do some self-study to perform well on the course assigned projects.
Gallery
1. Linear Regression Research (30 points)
Click the Blue logo below to open colab, or click here. I prefer if you submit in Colab (link), make sure you save your progress. However, if you have to, I wouldn’t mind to much if you do it on your own machine and send me the IPYNB.
Student Questions:
I had a question about the first question on the homework. In the question, you ask for Tesla and S&P returns, is this just the stock price at close or is this something else? Thanks in advance.
F. Industry Factors (HW1)
The introduction starts with (1) an overview of some basic machine learning concepts, (2) the history of machine learning in finance, (3) how machine learning is currently applied to finance, (4) and an introduction to one of the first machine learning methods, known as linear regression, and (5) your first project.