Week 47: From Decision Trees to Ensemble Methods, Random Forests and Boosting Methods and Summary of Course

 

 

 

Machine learning

The following topics will be covered

  1. Linear methods for regression and classification:
    1. Ordinary Least Squares
    2. Ridge regression
    3. Lasso regression
    4. Logistic regression
  2. Neural networks and deep learning:
    1. Feed Forward Neural Networks
    2. Convolutional Neural Networks
    3. Recurrent Neural Networks
  3. Decisions trees and ensemble methods:
    1. Decision trees
    2. Bagging and voting
    3. Random forests
    4. Boosting and gradient boosting
  4. Support vector machines, not covered this year but included in notes
    1. Binary classification and multiclass classification
    2. Kernel methods
    3. Regression