Chapter 1

Introduction

What is Machine Learning?

medium • 1 min read

Supervised vs Unsupervised learning

medium • 2 min read

Applications of ML

medium • 3 min read

Hypothesis space and Inductive bias

medium • 4 min read

Evaluation metrics

medium • 5 min read

Chapter 2

Supervised Learning

Linear regression

medium • 1 min read

Logistic regression

medium • 2 min read

Support Vector Machines (SVM)

medium • 3 min read

K-Nearest Neighbors (KNN)

medium • 4 min read

Naive Bayes classifier

medium • 5 min read

Chapter 3

Unsupervised Learning

Clustering algorithms

medium • 1 min read

K-means clustering

medium • 2 min read

Hierarchical clustering

medium • 3 min read

Principal Component Analysis (PCA)

medium • 4 min read

Dimensionality reduction

medium • 5 min read

Chapter 4

Artificial Neural Networks

Perceptron model

medium • 1 min read

Multi-layer perceptron

medium • 2 min read

Backpropagation algorithm

medium • 3 min read

Activation functions

medium • 4 min read

Introduction to Deep Learning

medium • 5 min read

Chapter 5

Ensemble Methods

Bagging

medium • 1 min read

Random Forests

medium • 2 min read

Boosting (AdaBoost, Gradient Boosting)

medium • 3 min read

Stacking

medium • 4 min read

Model evaluation and selection

medium • 5 min read