Machine Learning Crash Course

Get a quick overview of the important topics in Machine Learning, with a strong focus on practically applying what you learn.

1Supervised Learning

Regression - Linear, Multiple Linear, Polynomial, Support Vectors, Decision Trees, Random Forests

Classification - Naive Bayes, Decision Trees, Random Forests, Logistic Regression, Support Vectors, K-NN

2Unsupervised Learning

K-Means Clustering

DBSCAN

3Ensemble Learning

Ensemble Learning Techniques - Voting, Average, Weighted Average

Boosting/Bagging - XGBoost, AdaBoost, Gradient Descent