Supervised Learning

• Linear Regression
  • A method for predicting a continuous target variable based on one or more input features.
• Classification
  • A technique for assigning input data into predefined categories or classes.
  • Decision Trees
    • A greedy algorithm. Use parameters to separate and classify data.
  • KNN
  • Logistic Regression
    • A regression model used for binary classification that predicts the probability of a class.
  • Newton's Method
    • An optimization algorithm used to find the parameters that minimize the cost function in logistic regression and other models.
  • Support Vector Machines
    • A powerful classification method that finds the hyperplane that best separates the classes in the feature space.

Resources and Misc

This class is/was taken at UT Dallas: CS 4375 Introduction to Machine Learning and taught by Erick Parolin.

For extra resources and notes, you can take a look at the Standford Open Course.

Note: Because of the use of external resources, the notation will differ, because of this, I will be following the notation from the Stanford course, just in case if I ever want to go back and reread the material, but the general idea should be the same.