Introduction to Machine Learning

Description

In this course, you will learn:

• Mathematical prerequisites and an introduction to machine learning.
• Types of regression (linear, polynomial, multi variable regression).
• Logistic regression, Nave Bayes, and K-nearest neighbours are three classification algorithms.
• Hierarchical and k-means clustering are two approaches for clustering.

Syllabus:

1. Introduction to machine learning and mathematical prerequisites.
2. Regression (linear, polynomial, multivariable regression).
3. Logistic regression. 
4. Naïve Bayes and K-nearest neighbors.
5. Clustering methods: hierarchical and k-means clustering.