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MATLAB for Machine Learning and Chemometrics

Course Description

MATLAB, a contraction of “Matrix Laboratory”, is a great environment for working with large quantities of data such as that found in most chemical data science applications. MATLAB for Machine Learning and Chemometrics covers the basic MATLAB operations needed to use Eigenvector’s  PLS_Toolbox software for data modeling. Data import, plotting and getting help are also covered in this half-day course. Students will also learn to write basic scripts and functions, thus opening the door to programming custom routines for data analysis. We’ll also show how we integrated routines from Python so you can access them without learning an additional language.

Prerequisites

Linear Algebra for Machine Learning and Chemometrics or equivalent experience.

Course Outline

  1. Introduction
    1. What is MATLAB
    2. History
    3. Versions
  2. Starting MATLAB
    1. The Desktop: Command WIndow, History, Current Folder, Workspace
    2. Help Browser, Editor, Path Tool
  3. The Workspace
    1. Entering data, types of data and the DataSet Object
    2. Simple Command Line operations
  4. Saving, clearing and importing data
  5. Command Line functions and help
    1. Starting and using GUIs
    2. Plotting and graphics
  6. Using functions and scripts
    1. Differences between scripts and functions
    2. Writing scripts
    3. Writing functions
  7. Accessing Python routines from MATLAB
    1. How Python routines are integrated into PLS_Toolbox/Solo
    2. Calling Python routines directly