CatBoost: Categorical Boosting
CatBoost natively handles categorical features without encoding. Complete guide with ordered boosting, Python code.
CatBoost: Categorical Boosting LireLearn Python
Explore in-depth articles on programming, analyses of innovative GitHub projects, and guides on advanced Python frameworks and techniques.
LightGBM: Fast and Lightweight Gradient Boosting
LightGBM is a gradient boosting optimized for speed and memory efficiency. Complete guide with GOSS, EFB, and Python code.
LightGBM: Fast and Lightweight Gradient Boosting Lire
XGBoost: Extreme Gradient Boosting
XGBoost is the most performant boosting algorithm for tabular data. Complete guide with parallel trees, regularization, and Python code.
XGBoost: Extreme Gradient Boosting Lire
Extra Trees: Extremely Randomized Trees
Extra Trees pushes Random Forest’s randomness further with completely random splits. Complete guide with Python code.
Extra Trees: Extremely Randomized Trees Lire
Random Forest: Random Forest
Random Forest is an ensemble of decision trees using bagging. Complete guide with random features, OOB score, and Python code.
Random Forest: Random Forest Lire
Elastic Net: Combined L1 + L2 Regularization
Elastic Net combines L1 (Lasso) and L2 (Ridge) regularization for performant regression. Complete guide with Python code.
Elastic Net: Combined L1 + L2 Regularization Lire
SVM (Support Vector Machine): Support Vector Machine
SVM finds the optimal hyperplane that maximizes the margin between classes. Complete guide with kernel trick, C, gamma, and Python code.
SVM (Support Vector Machine): Support Vector Machine Lire
QDA (Quadratic Discriminant Analysis): Quadratic Discriminant Analysis
QDA is like LDA but with one covariance per class, enabling quadratic boundaries. Complete guide with Python code.
QDA (Quadratic Discriminant Analysis): Quadratic Discriminant Analysis Lire
LDA (Linear Discriminant Analysis): Linear Discriminant Analysis
LDA maximizes separation between classes while minimizing within-class variance. Complete guide with math and Python code from scratch.
LDA (Linear Discriminant Analysis): Linear Discriminant Analysis Lire
KNN (K-Nearest Neighbors): Classification by Proximity
KNN classifies a point based on the majority of its k nearest neighbors. Complete guide with distance metrics, weighting, and Python code.
KNN (K-Nearest Neighbors): Classification by Proximity Lire