optimization: videos

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1. 1▶Convex SetsSteve BruntonNotes
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2. 2▶Convexity 101 [Optimization Bootcamp]Steve BruntonNotes
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3. 3▶Applications of OptimizationSteve BruntonNotes
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4. 4▶The Anatomy of an Optimization ProblemSteve BruntonNotes
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5. 5▶Optimization: A Bootcamp for Machine Learning, Inverse Problems, and ControlSteve BruntonNotes
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6. 6▶Bayesian Linear Regression [Python Example]Steve BruntonNotes
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7. 7▶Bayesian Linear Regression and Maximum a Posteriori (MAP) EstimateSteve BruntonNotes
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8. 8▶Bayesian Linear Regression and Maximum Likelihood EstimatesSteve BruntonNotes
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9. 9▶Monte Carlo Sampling and Bootstrapping in Bayesian InferenceSteve BruntonNotes
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10. 10▶Density Estimation with Gaussian Mixture Models (GMM) and Empirical PriorsSteve BruntonNotes
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11. 11▶Conjugate Priors Example: Normal Distribution and the Exponential Family of DistributionsSteve BruntonNotes
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12. 12▶Bayesian Updates and Conjugate PriorsSteve BruntonNotes
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13. 13▶Bayesian Inference: OverviewSteve BruntonNotes
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14. 14▶Properties of Chi-Squared and Student's t DistributionsSteve BruntonNotes
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15. 15▶Hypothesis Testing Revisited: Normal, t, and Chi-Squared Distribution TestsSteve BruntonNotes
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16. 16▶6.8210 Spring 2024 Lecture 24: Imitation learning / Foundation models / Course wrap-upunderactuatedNotes
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17. 17▶6.8210 Spring 2024 Lecture 23: Feedback motion planningunderactuatedNotes
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18. 18▶6.8210 Spring 2024 Lecture 22: Output feedbackunderactuatedNotes
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19. 19▶6.8210 Spring 2024 Lecture 21: Robust Control & Policy SearchunderactuatedNotes
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20. 20▶6.8210 Spring 2024 Lecture 20: Stochastic ControlunderactuatedNotes
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21. 21▶6.8210 Spring 2024 Lecture 19: Stochastic dynamicsunderactuatedNotes
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22. 22▶6.8210 Spring 2024 Lecture 18: Sampling-based (kinodynamic) motion planningunderactuatedNotes
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23. 23▶6.8210 Spring 2024 Lecture 17: Mixed-discrete (combinatorial) and continuous optimizationunderactuatedNotes
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24. 24▶6.8210 Spring 2024 Lecture 16: Humanoid RobotsunderactuatedNotes
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25. 25▶6.8210 Spring 2024 Lecture 15: Planning + Control Through ContactunderactuatedNotes
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26. 26▶6.8210 Spring 2024 Lecture 14: Hybrid Trajectory OptimizationunderactuatedNotes
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27. 27▶6.8210 Spring 2024 Lecture 12: Trajectory StabilizationunderactuatedNotes
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28. 28▶6.8210 Spring 2024 Lecture 11: Trajectory Optimization IIunderactuatedNotes
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29. 29▶6.8210 Spring 2024 Lecture 10: Trajectory Optimization IunderactuatedNotes
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30. 30▶6.8210 Spring 2024 Lecture 9: Computing Lyapunov Functions IIunderactuatedNotes
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