Machine Learning Tutorial

Tutorials for new students in computational chemistry

Classification Machine Learning for Computational Chemistry

Below are some interactive tutorials that will explain various necessary tools/algorithms/APIs for you to make your very own machine learning model, including a tutorial for a demonstrative fully functional machine learning model that can classify cancerous PAH molecules. Just click on the tutorial title with the most interesting description, and use the home button and about button to navigate.

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Tutorial 2. Training the Machine Learning Model

Learning Objectives

  • Use Scikit-learn for simple classification tasks
  • Use RDKit for molecular representations, such as Morgan Fingerprint
  • Use the ROC curve to represent model accuracy
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Tutorial 1. Configuring the Data Set

Learning Objectives

  • Understand the basics of Chemoinformatics
  • Interpret the raw dataset
  • Use APIs like PubChem and RDKit to transform data
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