Explore Tutorials by Topic
Regression
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 →Classification
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 →Support Vector Machines
Learn how support vector machines 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 →Other Basic Machine Learning Methods
K-Means Clustering
Learn how K-means works, how to choose k, and apply it to real datasets.
Read Tutorial →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 →Reinforcement Learning
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 →Further Methods In Machine Learning
Bayesian Inference with Pyro
Learn how Bayesian Inference can be used to develop more robust models and even fix missing data without lazy data imputation fix arounds.
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