Machine Learning Cookbook
Interactive educational resource for exploring machine learning algorithms with detailed mathematical foundations, implementations, and visualizations.
Algorithm Categories
Supervised Learning
Algorithms that learn from labeled training data
Classification
Regression
Unsupervised Learning
Algorithms that find patterns in unlabeled data
Clustering
Dimensionality Reduction
Ensemble Methods
Combine multiple models for better performance
Bagging
Boosting
Select Algorithm
Logistic Regression
Probabilistic classification algorithm using sigmoid activation
Classification
Probabilistic
Linear Model
Linear Regression
Predicts continuous values using linear relationships
Regression
Linear Model
Least Squares
K-Means Clustering
Partitions data into k clusters based on similarity
Clustering
Unsupervised
Centroid-based
Support Vector Machine
Finds optimal hyperplane with maximum margin
Classification
Margin Maximization
Kernel Trick
Decision Tree
Tree-structured decision model with interpretable rules
Classification
Regression
Tree-based
Random Forest
Ensemble of decision trees with random feature selection
Ensemble
Bagging
Robust