| May 22, 2024 | Optimization Strategies in Modern Machine Learning (Non-Convexity, Hyperparameters, and Meta-Learning) |
| Jan 04, 2024 | Matrix Calculus for Data Science |
| Nov 12, 2023 | Regularization & Generalization in Optimization |
| Aug 21, 2023 | Adaptive Optimization — Adam, RMSProp, & Beyond |
| Jul 22, 2023 | Convexity, Constraints & Convergence Guarantees |
| Jul 15, 2023 | Taylor Expansions & Second-Order Thinking |
| Jul 01, 2023 | Optimization Foundations |
| Jun 05, 2023 | Multivariable Functions & Gradients |
| Feb 11, 2023 | Applied Probabilistic Modeling |
| Oct 28, 2022 | Linear Regression Models |
| Oct 17, 2022 | Information Theory, Correlation & Statistical Learning Theory |
| Oct 12, 2022 | Expectation-Maximization (EM) for Unsupervised Learning |
| Aug 03, 2022 | Markov Chains, Hidden Markov Models & Probabilistic Sequence Modeling |
| Jul 13, 2022 | Statistical Inference (Sampling, Confidence Intervals & Hypothesis Testing) |
| Jun 10, 2022 | Bayesian Thinking, MLE, MAP & Inference |
| Jun 05, 2022 | Probability Distributions |
| Jun 01, 2022 | Foundations of Probability |
| Feb 07, 2022 | Linear Algebra - Bonus Topics |
| Feb 07, 2022 | Vector Spaces and Transformations |
| Feb 03, 2022 | Eigenvalues, Eigenvectors, and Singular Value Decomposition |
| Jan 20, 2022 | Systems of Linear Equations |
| Jan 15, 2022 | Matrices and Matrix Operations |
| Jan 13, 2022 | Vector Operations, Norms, and Projections |