This tutorial explores machine learning using sci-kit learn and tensorflow for applications in particle physics.


For this tutorial we will be using kaggle. Make sure you have created an account Please read the first three sections before coming to the tutorial:

  • Introduction
  • Mathematical Foundations
  • Resources We will briefly review these sections in the tutorial. Note that they mostly cover the mathematical foundations of machine learning; there is no coding involved in these sections.


Setup Download files required for the lesson
00:00 1. Introduction What is machine learning?
What role does machine learning have in particle physics?
What should I do if I want to get good at machine learning?
00:00 2. Mathematical Foundations What is the common terminology in machine learning?
00:00 3. Resources Where should I go if I want to get better at python?
What are the machine learning libraries in python?
Where should I go if I want to get better at machine learning?
00:10 4. Data Discussion and Preprocessing What dataset is being used
How must we organize our data such that it can be used in the machine learning libraries?
00:25 5. Model Training How does one train machine learning models in python?
00:45 6. Model Comparison How do you use the sci-kit learn and tensorflow packages for machine learning?
01:05 7. Neural Networks What is a neural network?
How can I visualize a neural network?
01:15 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.