Skip to content

Latest commit

 

History

History
10 lines (7 loc) · 971 Bytes

README.md

File metadata and controls

10 lines (7 loc) · 971 Bytes
Raw

cmac_coding_ml

This is the course given to the CMAC PhD students to give them an introduction to Python and also machine learning. The course materials are as follows:

  • There are 3 IPython notebooks (.ipynb files), the order in which to work through them is: intro_to_python, data_analysis and machine_learning.
  • The solutes directory contains the dataset used throughout the exercises to explore, combine and perform machine learning on a dataset containing varying solvents, solutes and their molecular descriptors. The main idea being the ability to predict solubility of a solute in a solvent from the molecular descriptors.
  • The presentations directory contains the slides presented at the course.
  • The solutions directory contains the solutions (well my solutions, coding structure varies per person) to the exercises presented in the three notebooks.

This course was designed for anyone who has never used Python before and is unfamiliar with ML.