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Introduction to Machine Learning with Python

The course on which the project will focus is PHY426H5 Computational Modeling in Physics (SCI) in the Spring semester of 2019.

These lecture and practical are created for CPS Teaching Fellowship where we introduce a novel approach to study advanced scientific programming. The goal of the lecture is to introduce Machine Learning (ML) tools and how to use them for Molecular Dynamics simulations in Python programmming language. We will use a lot of numpy functions and a few of new modules, such as sklearn for dimensionality reduction. Important concepts that we will cover:

Lecture:

  • Supervised and unsupervised machine learning
  • Dimensionality reduction
  • Principal Component Analysis (PCA)
  • Multidimensional Scaling (MDS)

Practical:

  • Application of PCA to MD simulations to study folding
  • Application of MDS to build the Old World Map