AI Tutorials

← Back to Home

Explore Tutorials by Topic

Chapter 1: Regression

Regression Analysis

Understand the basics of performing regression on data.

Read Tutorial →

Linear Regression

Understand the basics of linear regression, it's solution and how to code it in python.

Read Tutorial →

Polynomial Regression

Learn how to model nonlinear relationships using polynomial regression.

Read Tutorial →

Elastic Net

Learn how Elastic Net regression blends L1 and L2 regularization to handle feature selection and multicollinearity, with step-by-step guidance and practical implementation.

Read Tutorial →

Chapter 2: Classification

Classification

A short introduction to the problem of classification.

Read Tutorial →

Logistic Regression

Explore binary classification using logistic regression and the sigmoid function.

Read Tutorial →

Softmax Regression

Learn how Softmax Regression extends logistic regression to multi-class classification, with a clear explanation of the math, gradients, and hands-on implementation.

Read Tutorial →

Linear Discriminant Analysis

Learn how LDA can be used for both classification and dimensionality reduction and the link between the two approaches.

Read Tutorial →

Quadratic Discriminant Analysis

Learn how QDA can be used for classification.

Read Tutorial →

Support Vector Machines

Learn how support vector machines can be used to solve classification problems.

Read Tutorial →

Naive Bayes

Learn how Naive Bayes can be used to solve classification problems.

Read Tutorial →

Perceptron

Learn how the most basic element of neural netowrks can perform binary classification.

Read Tutorial →

Trees and Random Forests

Learn how decision trees and their extension to an ensemble method called random forest can be used to solve classification problems.

Read Tutorial →

Chapter 3: Other Machine Learning Methods

K-Means Clustering

Learn how K-means works, how to choose k, and apply it to real datasets.

Read Tutorial →

K-Nearest Neighbors

Learn how KNN works and apply it to real datasets.

Read Tutorial →

Chapter 4: Neural Networks

Intro to Neural Networks

Build your first neural network from scratch and understand how it learns.

Read Tutorial →

YOLO: Real-Time Object Detection

Dive into the architecture of YOLO and how it detects objects in real-time.

Read Tutorial →

Chapter 5: Reinforcement Learning and Learning to Play Games

Monte Carlo Tree Search

Learn how the monte carlo tree search algorithm works and play against it in connect four!

Read Tutorial →

AlphaZero

Learn how this famous algorithm from google deepmind works and how it improves on the Monte carlo tree search algorithm. Also vs it in connect four!

Read Tutorial →