bayesian linear: videos

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1. 1▶HydroGym: A Reinforcement Learning Platform for Fluid DynamicsSteve BruntonNotes
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2. 2▶Convex SetsSteve BruntonNotes
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3. 3▶Convexity 101 [Optimization Bootcamp]Steve BruntonNotes
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4. 4▶Applications of OptimizationSteve BruntonNotes
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5. 5▶The Anatomy of an Optimization ProblemSteve BruntonNotes
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6. 6▶Optimization: A Bootcamp for Machine Learning, Inverse Problems, and ControlSteve BruntonNotes
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7. 7▶Bayesian Linear Regression [Python Example]Steve BruntonNotes
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8. 8▶Bayesian Linear Regression and Maximum a Posteriori (MAP) EstimateSteve BruntonNotes
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9. 9▶Bayesian Linear Regression and Maximum Likelihood EstimatesSteve BruntonNotes
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10. 10▶Monte Carlo Sampling and Bootstrapping in Bayesian InferenceSteve BruntonNotes
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11. 11▶Density Estimation with Gaussian Mixture Models (GMM) and Empirical PriorsSteve BruntonNotes
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12. 12▶Conjugate Priors Example: Normal Distribution and the Exponential Family of DistributionsSteve BruntonNotes
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13. 13▶Bayesian Updates and Conjugate PriorsSteve BruntonNotes
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14. 14▶Bayesian Inference: OverviewSteve BruntonNotes
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15. 15▶Properties of Chi-Squared and Student's t DistributionsSteve BruntonNotes
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16. 16▶Hypothesis Testing Revisited: Normal, t, and Chi-Squared Distribution TestsSteve BruntonNotes
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17. 17▶Lecture 16. Gibbs SamplingStatistical Computing, Fall 2017Notes
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18. 18▶Lecture15. Importance SamplingStatistical Computing, Fall 2017Notes
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19. 19▶Lecture 13. Introduction to Monte Carlo Methods and Random Variable GenerationStatistical Computing, Fall 2017Notes
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20. 20▶Lecture 12. Implementation of Bayesian Regression and Variable SelectionStatistical Computing, Fall 2017Notes
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21. 21▶Lecture 11. Bayesian Linear Regression (continued)Statistical Computing, Fall 2017Notes
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22. 22▶Lecture 10. Linear Bayesian RegressionStatistical Computing, Fall 2017Notes
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23. 23▶Lecture 9. Introduction to Bayesian Linear Regression, Model Comparison and SelectionStatistical Computing, Fall 2017Notes
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24. 24▶Lecture 8. Prior and Hierarchical ModelsStatistical Computing, Fall 2017Notes
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25. 25▶Lecture 7. Exponential Family, Generalized Linear Models, Inference for Multivariate GaussianStatistical Computing, Fall 2017Notes
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26. 26▶Lecture 6. Introduction to Bayesian Statistics, Exponential Family of DistributionsStatistical Computing, Fall 2017Notes
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