Machine Learning

This repository contains Jupyter notebooks implementing Machine Learning algorithms to solve different problems.

The notebooks use Scikit-learn and Python 3.6.9.

Table of contents

• 1 - Linear Regression with one variable
• 2 - Building Linear Regression with one variable: Step by Step
• 3 - Linear Regression with multiple variables
• 4 - Building Linear Regression with multiple variables: Step by Step
• 5 - Logistic Regression
• 6 - Building Logistic Regression: Step by Step
• 7 - Regularized Linear Regression
• 8 - Regularized Logistic Regression
• 9 - Support Vector Machines
• 10 - K-means Clustering
• 11 - Building K-means Clustering: Step by Step
• 12 - Principal Component Analysis
• 13 - Anomaly detection
• 14 - Recommender Systems