| Apr 26, 2022 | Machine Learning literatureML & Stats in 🔢 math |
| Apr 15, 2022 | Machine Learning coursesML & Stats in 🔢 math |
| Oct 14, 2021 | Elements of LearningML & Stats in 🔢 math |
| Sep 16, 2021 | Gradient Boosted Decision Trees: A RecapML & Stats in 🔢 math |
| Sep 13, 2021 | The Gaussian CheatsheetML & Stats in 🔢 math |
| Jul 9, 2021 | Topics in Bayesian Machine LearningML & Stats in 🔢 math |
| May 12, 2021 | Mathematics OverviewOverview in 🔢 math |
| Dec 28, 2020 | The Gibbs distribution and general BayesML & Stats in 🔢 math |
| Nov 17, 2020 | Why is Bayesian inference hard?ML & Stats in 🔢 math |
| Nov 10, 2020 | IntegraphsUncategorized in 🔢 math |
| Oct 18, 2020 | Topics in Numerical Linear AlgebraLinear Algebra in 🔢 math |
| Sep 28, 2020 | Orthogonal projectors and linear regressionLinear Algebra in 🔢 math |
| Aug 30, 2020 | Discovering Taylor series the hard wayLinear Algebra in 🔢 math |
| Aug 24, 2020 | Linear Algebra Done RightLinear Algebra in 🔢 math |
| Aug 23, 2020 | ML FragmentsResearch in 🔢 math |
| Jul 10, 2020 | An Introduction to Epipolar GeometryComputer vision in 🔢 math |
| Jul 5, 2020 | RL: Tricks of the TradeReinforcement learning in 🔢 math |
| Feb 2, 2020 | Deriving the Cross Entropy MethodReinforcement learning in 🔢 math |
| Mar 17, 2019 | The Stein GradientML & Stats in 🔢 math |
| May 21, 2018 | Policy Gradients in a NutshellReinforcement learning in 🔢 math |
| Feb 6, 2018 | When does SGD work well?ML & Stats in 🔢 math |
| Dec 4, 2017 | The beauty of Bayesian LearningML & Stats in 🔢 math |
| Oct 15, 2017 | Visualizing the Confusion MatrixML & Stats in 🔢 math |
| Oct 8, 2017 | The magic of Automatic DifferentiationML & Stats in 🔢 math |
| Jul 18, 2017 | A Primer on Projective GeometryComputer vision in 🔢 math |
| Jun 24, 2017 | Introduction to RANSACComputer vision in 🔢 math |
