Q1 Weekly Plan

Main Topics

  • Intro to Python (weeks 1-5)
  • Intro to the Mathematics of Machine Learning (weeks 1-5)
  • Linear Regression (week 3, 9-10)
  • Interpretation of results (weeks 2-3, 5, 8, 9)
  • Overview of Classical Machine Learning Approaches (weeks 2,3,8) *

Weekly Plan

  • Week 1
    • Install software (jupyter, intellij, colab, etc)
  • Week 2
    • Intro to pandas using weather datasets (Leesburg and London)
    • Baye’s Theorem
    • Goodness of Fit for categorical data
  • Week 3
    • Into to numpy
    • Linear Regression (computing coefficients from scratch)
    • Goodness of Fit for numerical data
  • Week 4
    • Matrix Operations
    • Coding matrix arithmetic in python and numpy
  • Week 5
    • Running Time analysis of Matrix multiply
    • Types of regression (linear, log-linear, log-log)
  • Week 6
    • Research topics
    • Book club
  • Week 7
    • PSAT?
    • Movable / free week
  • Week 8
    • Begin sci-kit learn
    • Mushroom dataset
    • Overview of several ML algorithms
  • Week 9
    • Deep dive into Linear Regression
    • Life Expectancy dataset
    • Correlated variables, multi-linear regression, normalization and regularization
    • Interpreting linear coefficients
  • Week 10
    • Finish Linear Reg
    • Introduce Principal Component Analysis
    • PCA to compress a picture
  • Week 11
    • Intro to Classification
    • Logistic Regression