Overview
Syllabus
Course Introduction.
Fundamentals of Machine Learning.
Supervised Learning and Unsupervised Learning In Depth.
Linear Regression.
Logistic Regression.
Project: House Price Predictor.
Regularization.
Support Vector Machines.
Project: Stock Price Predictor.
Principal Component Analysis.
Learning Theory.
Decision Trees.
Ensemble Learning.
Boosting, pt 1.
Boosting, pt 2.
Stacking Ensemble Learning.
Unsupervised Learning, pt 1.
Unsupervised Learning, pt 2.
K-Means.
Hierarchical Clustering.
Project: Heart Failure Prediction.
Project: Spam/Ham Detector.
Taught by
freeCodeCamp.org