Data Science
Comprehensive guide to Data Science concepts, from Statistics and Optimization to Machine Learning and Deep Learning
Welcome to the Data Science section. This section covers essential mathematical foundations, statistical concepts, machine learning algorithms, and deep learning principles using a rigorous, math-first approach.
Topics
- Statistics & Probability - MLE, MAP, Hypothesis Testing, and Information Theory
- Optimization - Gradient Descent, Lagrange Multipliers, and ADMM
- Linear Models - OLS, Ridge Regression, and Evaluation Metrics
- Machine Learning Algorithms - PCA, SVM, K-Means, KNN, and Dimensionality Reduction
- Neural Networks - Backpropagation, Activation Functions, and Architectures