Day 3: Classical and Quantum Machine Learning in Finance

An Introduction to Classical and Quantum Machine Learning

• Lecture 1: An Introduction to Machine Learning https://durham.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=1b839b43-f1c4-49fb-a8ac-ae42013da020

• Lecture 2: The Regression Algroithm https://durham.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=2b569402-6431-4d48-9c90-ae420164a708

• Lecture 3: An Introduction to Quantum Machine Learning https://durham.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=6e3ebcb6-3447-43a7-8ce9-ae42016f9f73

• Jupyter Notebook Python Regression Model Example: https://github.com/theheavygluon/QuantumFinance/blob/main/Day%203/Python%20Regression%20Model%20Example%20(1).ipynb

Please Note: All python code in this workbook is taken from the Tutorial Solutions on Linear Regression by Marc Deisenroth from his GitHub page; none of the code is my own, and the equations used are based off of his tutorial linked below

https://colab.research.google.com/github/mml-book/mml-book.github.io/blob/master/tutorials/tutorial_linear_regression.solution.ipynb#scrollTo=yr9AM8lWuYI0

• Lecture Notes: An Introduction to Classical and Quantum Machine Learning Lecture Notes.pdf

• Lecture Powerpoint Slides: An Introduction to Classical and Quantum Machine Learning PowerPoint Slides.pdf