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Part 01-Module 02-Lesson 02_Get Ready/05. The Great Robot Race-UFGu15hCtKg.mp4 315.9 MBPart 05-Module 01-Lesson 03_Project Optimize Histogram Filter/02. Nd113 Running The Project V1--X1pB-HTdnQ.mp4 84.3 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/01. Meet Danny Shapiro At Nvidia-tglLnJNHSI4.mp4 45.3 MBPart 02-Module 01-Lesson 11_Robot Localization/04. Total Probability-n1EacrqyCs8.mp4 42.4 MBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/06. More Kalman Filters-hUnTg5v4tDU.mp4 37.2 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/19. Kalman Filter Code-X7cixvcogl8.mp4 35.4 MBPart 02-Module 01-Lesson 11_Robot Localization/02. Introduction-Uqt_pRbR8rI.mp4 33.6 MBPart 02-Module 01-Lesson 11_Robot Localization/33. Bayes' Rule-sA5wv56qYc0.mp4 30.4 MBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/08. Kalman Filter Design-KYEr4BXhD_E.mp4 28.7 MBPart 05-Module 01-Lesson 01_C++ Intro to Optimization/04. Nd113 Embedded Terminal V1-Bhl5JQ_N9V8.mp4 27.8 MBPart 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/01. Meet Phantom Auto-D6-7L9nZMPY.mp4 27.8 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/02. Tracking Intro-8O9GV4SUToA.mp4 26.8 MBPart 06-Module 01-Lesson 01_How to Solve Problems/38. Solution Step III-CRv1ogJYe8w.mp4 26.2 MBPart 06-Module 01-Lesson 01_How to Solve Problems/33. Best Strategy-JsMwEH8cluU.mp4 25.8 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/17. Gaussian Motion-X7YggdDnLaw.mp4 25.7 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/48. Nd113 C7 46 L Evaluation Metrics-fDN4D1QV674.mp4 24.9 MBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/03. Kalman Filter Land-LXJ5jrvDuEk.mp4 23.7 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/13. Images as Grids of Pixels-RVNiaZuv6Ss.mp4 23.7 MBPart 02-Module 01-Lesson 04_Conditional Probability/11. Medical Example 2-FV_hc3MzS_8.mp4 23.1 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/37. Nd113 C7 33 L Features And Classification-Ni3ocWoUDPk.mp4 22.7 MBPart 01-Module 01-Lesson 01_Introduction/01. Final Teaser ISDC-j7iB0p4dOj4.mp4 22.6 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/35. Nd113 C7 32 L Average Brightness V2-oUlOS670uQg.mp4 22.2 MBPart 02-Module 01-Lesson 06_Bayes' Rule/08. Cancer Test-CNpSrdnYvbo.mp4 18.9 MBPart 02-Module 01-Lesson 11_Robot Localization/03. Localization-31xZhj2uPr4.mp4 18.7 MBPart 02-Module 01-Lesson 11_Robot Localization/35. Theorem of Total Probability-byZ-BzbQA5M.mp4 18.7 MBPart 02-Module 01-Lesson 11_Robot Localization/27. Sense and Move 2-rmWL_3r8MKo.mp4 18.4 MBPart 06-Module 01-Lesson 01_How to Solve Problems/36. Solution Step I-bIZgt0ttMeU.mp4 18.3 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/12. Parameter Update-d8UrbKKlGxI.mp4 18.2 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/03. Gaussian Intro-GHKKUR6tZE0.mp4 17.9 MBPart 02-Module 01-Lesson 11_Robot Localization/23. Limit Distribution Quiz-SXSafquSoW8.mp4 17.9 MBPart 02-Module 01-Lesson 06_Bayes' Rule/26. Bayes Rule Summary-RgXQ8GRsjfc.mp4 17.7 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/40. High Pass Filters-JOa9ZtV_rB4.mp4 17.1 MBPart 06-Module 01-Lesson 01_How to Solve Problems/18. Algorithm Pseudocode-Ei91QeYiG_E.mp4 16.9 MBPart 06-Module 01-Lesson 01_How to Solve Problems/09. What Are the Inputs-cAr-unfe-mg.mp4 16.6 MBPart 02-Module 01-Lesson 04_Conditional Probability/23. Summary-yepMH9VswI8.mp4 16.6 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/07. Image Classification Pipeline-jfu6aqvU1vQ.mp4 16.4 MBPart 02-Module 01-Lesson 11_Robot Localization/26. Sense and Move-K8g3Hss8Q1A.mp4 16.2 MBPart 02-Module 01-Lesson 11_Robot Localization/19. Inexact Motion 1-C3f-T9_GTpw.mp4 15.8 MBPart 02-Module 01-Lesson 06_Bayes' Rule/09. Prior And Posterior-o2Tpws5C2Eg.mp4 15.7 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/29. Labeled Data and Accuracy-FN96OM_JGyM.mp4 15.4 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/10. Shifting the Mean-8c479K2UCZo.mp4 15.3 MBPart 06-Module 01-Lesson 01_How to Solve Problems/30. Step Three daysBetweenDates-DOkkOsraobw.mp4 15.3 MBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/04. Kalman Filter Prediciton-HTL5-0DDqE4.mp4 14.9 MBPart 02-Module 01-Lesson 11_Robot Localization/08. Probability After Sense-UFcTLCttNRI.mp4 14.7 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/04. Nd113 C7 02 L Introducing Tarin V2-us2b__pBR8Y.mp4 14.7 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/09. Learning To Classify Images-_mE0nkLPSw0.mp4 14.3 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/25. Nd113 C7 23 L HSV Conversion-GbrJi0U8T20.mp4 14.0 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/19. Kalman Filter Code-3xBycKfnCOQ.mp4 13.9 MBPart 04-Module 01-Lesson 01_C++ Getting Started/15. Two Functions Same Name-9SgmzOfBmRU.mp4 13.8 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/43. Nd113 C7 40 L Convolution In Self-Driving Cars-nz7rOTZ99X4.mp4 13.7 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/02. Computer Vision and Sebastian-pil3PeZzCIY.mp4 13.7 MBPart 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/02. Nd113 C6 L1 01 Inertial Navigation V1 (1)-vWgG0d2HOVE.mp4 13.5 MBPart 02-Module 01-Lesson 11_Robot Localization/13. Sense Function-eIjyrQpDogg.mp4 13.5 MBPart 02-Module 01-Lesson 04_Conditional Probability/21. Two Coins 3-JIWv5fU3GLA.mp4 13.5 MBPart 05-Module 01-Lesson 02_C++ Optimization Practice/16. Nd113 Story 1 V1-lIe2zso8A-w.mp4 13.4 MBPart 02-Module 01-Lesson 06_Bayes' Rule/14. Bayes Rule Diagram-b8M9CWxRyQ4.mp4 13.1 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/20. Kalman Prediction-doyrdLJ6rJ4.mp4 13.0 MBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/02. Kalman Prediction-doyrdLJ6rJ4.mp4 13.0 MBPart 06-Module 01-Lesson 01_How to Solve Problems/24. Define Simple nextDay-Qttkfhh3I5s.mp4 12.6 MBPart 04-Module 01-Lesson 01_C++ Getting Started/04. Why C++-_t4ZvwfnuCA.mp4 12.6 MBPart 06-Module 01-Lesson 01_How to Solve Problems/23. What Should We Write First-HRepefDqkDM.mp4 12.5 MBPart 02-Module 01-Lesson 11_Robot Localization/21. Inexact Motion 3-7T1Rr7KLgdM.mp4 12.4 MBPart 04-Module 01-Lesson 01_C++ Getting Started/16. Function Signatures 1-T6kQ_4w98IQ.mp4 12.2 MBPart 02-Module 01-Lesson 04_Conditional Probability/18. Total Probability-YSYpzFR4k1I.mp4 12.1 MBPart 02-Module 01-Lesson 06_Bayes' Rule/27. Robot Sensing 1-_DjfTytro6I.mp4 12.0 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/22. Nd113 C7 20 L Green Screen Car V2-_YEdV_mRKXQ.mp4 11.9 MBPart 02-Module 01-Lesson 03_Probability/06. Flipping Coins-OpNufHYgJCg.mp4 11.9 MBPart 02-Module 01-Lesson 03_Probability/24. Doubles-fkUyTJNbdzU.mp4 11.8 MBPart 02-Module 01-Lesson 03_Probability/22. One Of Three 2-27Ed1GI4j84.mp4 11.8 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/27. Nd113 C7 25 L Day And Night Classification NEEDS ANM V1-bsra6mwtw7U.mp4 11.7 MBPart 02-Module 01-Lesson 06_Bayes' Rule/36. Sebastian At Home-R4zq6mPPMxs.mp4 11.6 MBPart 02-Module 01-Lesson 11_Robot Localization/37. Two Coin Quiz-_AhoOd8YUK0.mp4 11.6 MBPart 02-Module 01-Lesson 11_Robot Localization/18. Move Function-TnFq6hufsYs.mp4 11.5 MBPart 02-Module 01-Lesson 04_Conditional Probability/20. Two Coins 2-hoVOT8qcQ7c.mp4 11.5 MBPart 06-Module 01-Lesson 01_How to Solve Problems/04. Days Between Dates-VLrJ01wEajw.mp4 11.4 MBPart 06-Module 01-Lesson 03_The Search Problem/33. Sliding Blocks Puzzle 2-7vExAvX3LbI.mp4 11.4 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/01. Introduction-XZL934YQ-FQ.mp4 11.2 MBPart 04-Module 01-Lesson 04_C++ Object Oriented Programming/03. Why Use Object Oriented Programming-G2KzZfNu9Ak.mp4 11.2 MBPart 06-Module 01-Lesson 01_How to Solve Problems/28. Step One Pseudocode-hJzpU5qC3hs.mp4 11.1 MBPart 06-Module 01-Lesson 01_How to Solve Problems/37. Solution Step II-SGC8UAz12Q4.mp4 11.1 MBPart 04-Module 01-Lesson 01_C++ Getting Started/06. Static Vs Dynamic Typing-D7v6iIAORkE.mp4 11.0 MBPart 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/10. L1 09 V2-b-zB9Bs8zKQ.mp4 10.9 MBPart 06-Module 01-Lesson 03_The Search Problem/05. Tree Search-lCuwrHKxNlU.mp4 10.8 MBPart 06-Module 01-Lesson 01_How to Solve Problems/14. The Expected Output-trokjJravhc.mp4 10.8 MBPart 06-Module 01-Lesson 01_How to Solve Problems/16. Try an Example-X29RjzKHsWU.mp4 10.7 MBPart 02-Module 01-Lesson 11_Robot Localization/28. Localization Summary-MVbo4OAgQCc.mp4 10.6 MBPart 02-Module 01-Lesson 11_Robot Localization/34. Cancer Test-SZ6Jg1wS604.mp4 10.6 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/32. Nd113 C7 29 L Features-HshygbfQylA.mp4 10.5 MBPart 02-Module 01-Lesson 06_Bayes' Rule/30. Robot Sensing 4-vasdN2Gol0M.mp4 10.4 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/50. Nd113 C7 47 L Outro-YbWjhAVvdKc.mp4 10.3 MBPart 06-Module 01-Lesson 03_The Search Problem/23. More Uniform Cost-8xH-3WtswDs.mp4 10.3 MBPart 02-Module 01-Lesson 04_Conditional Probability/08. Dependent Things-NDL-rxSYJWo.mp4 10.3 MBPart 06-Module 01-Lesson 01_How to Solve Problems/06. First Step-N8dKtrrCZ7U.mp4 10.3 MBPart 02-Module 01-Lesson 11_Robot Localization/26. Sense and Move-1s2dRczcu1A.mp4 10.2 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/15. Color Images--XbXiiGQ9gw.mp4 10.1 MBPart 02-Module 01-Lesson 11_Robot Localization/20. Inexact Motion 2-jR7FERpsqe4.mp4 10.0 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/16. New Mean and Variance-yo8jf0U4hlc.mp4 9.9 MBPart 06-Module 01-Lesson 01_How to Solve Problems/21. Simple Mechanical Algorithm-gPfkboHV3QA.mp4 9.9 MBPart 02-Module 01-Lesson 11_Robot Localization/36. Coin Flip Quiz-ASUXN9Ay35M.mp4 9.8 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/51. Ends and Beginnings-lCUkFi4fwLY.mp4 9.7 MBPart 02-Module 01-Lesson 06_Bayes' Rule/19. Normalizing Probability-yYqN9Mf4jqw.mp4 9.7 MB
Part 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/img/self-driving-uber-prototype-in-san-francisco.jpg 9.7 MBPart 02-Module 01-Lesson 03_Probability/25. Summary-hIEDvyCETEw.mp4 9.5 MBPart 02-Module 01-Lesson 03_Probability/21. One Of Three 1-bDCXSxkochE.mp4 9.5 MBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/15. L2 18 V2-nCJQl2kH8bY.mp4 9.4 MBPart 02-Module 01-Lesson 11_Robot Localization/23. Limit Distribution Quiz-kfPWiMsnWFI.mp4 9.3 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/31. Feature Extraction-DkmLO7PKhy8.mp4 9.3 MBPart 09-Module 01-Lesson 01_Congratulations! You've finished!/01. Congratulations on completing Intro to Self-Driving Cars!-w640r8wujPw.mp4 9.2 MBPart 02-Module 01-Lesson 11_Robot Localization/18. Move Function-wfjE0mVADIk.mp4 9.1 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/02. Tracking Intro-lDykH1UHq38.mp4 9.1 MBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/07. Approximating The Integral-9C05AHzI_I8.mp4 9.0 MBPart 01-Module 01-Lesson 01_Introduction/03. Meet The Team-U7OiT5kWlnQ.mp4 9.0 MBPart 02-Module 01-Lesson 01_Introduction/01. The Wonderland of Probability and Bayes' Rule-gfFWpMehzpk.mp4 8.9 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/18. Pre-processing--h1GS0SEyzY.mp4 8.9 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/07. Maximize Gaussian-fRYtUP0P4Lg.mp4 8.7 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/10. What Is Machine Learning-3mzV7uQhEos.mp4 8.7 MBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/01. L2 01 V2-GRgbA3XBy6w.mp4 8.7 MBPart 06-Module 01-Lesson 01_How to Solve Problems/22. Don't Optimize Prematurely-uQDk8euwyDI.mp4 8.6 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/04. Variance Comparison-rczAG7meAY4.mp4 8.6 MBPart 02-Module 01-Lesson 04_Conditional Probability/22. Two Coins 4-9R44IyZ-aQI.mp4 8.6 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/03. Welcome To Computer Vision-qAGnachIrxs.mp4 8.5 MBPart 06-Module 01-Lesson 03_The Search Problem/04. Example Route Finding-5lrkPKQwOFE.mp4 8.5 MBPart 04-Module 01-Lesson 01_C++ Getting Started/17. Function Signatures 2-Sx4AWTmXl2U.mp4 8.5 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/05. Nd113 C7 03 L Vision And SelfDriving Cars V1-dezDkQ47NaY.mp4 8.5 MBPart 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/07. Power of Trigonometry-yLMTfBq_I3k.mp4 8.4 MBPart 04-Module 01-Lesson 03_Practical C++/01. Introduction To Compilation-dyzGEB8YDGg.mp4 8.3 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/39. Nd113 C7 36 L Filters And Finding Edges V1-f3H2EtiZLOQ.mp4 8.3 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/13. Parameter Update 2-_AAkw_fynwc.mp4 8.2 MBPart 05-Module 01-Lesson 01_C++ Intro to Optimization/02. C Opt 01 L V2-Kdx1_BI5ddc.mp4 8.1 MBPart 02-Module 01-Lesson 06_Bayes' Rule/36. Sebastian At Home-TtmQ7YCw_1Y.mp4 8.1 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/20. Nd113 C7 19 L Color Masking-4U5fYTbSDg0.mp4 8.1 MBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/12. Working with Real Data-WvEcWtAz-OQ.mp4 8.0 MBPart 01-Module 01-Lesson 01_Introduction/09. Intro to Self-Driving Cars Expectations for this Nanodegree-TTOhBB7QaUg.mp4 8.0 MBPart 02-Module 01-Lesson 11_Robot Localization/15. Test Sense Function-Lf2DYUCsUH4.mp4 7.9 MBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/10. Nd113 C2 L3 08 L The Kalman Filter Equations V2-X9UUpk5URuw.mp4 7.9 MBPart 02-Module 01-Lesson 01_Introduction/02. Course Overview-QTFIJNBXx9w.mp4 7.8 MBPart 06-Module 01-Lesson 03_The Search Problem/31. Sliding Blocks Puzzle-Dzah_49isp8.mp4 7.8 MBPart 02-Module 01-Lesson 11_Robot Localization/22. Inexact Move Function-QCnPJcNprEU.mp4 7.8 MBPart 04-Module 01-Lesson 01_C++ Getting Started/02. Lesson Overview C++-lR3PH3bL-9U.mp4 7.8 MBPart 02-Module 01-Lesson 11_Robot Localization/13. Sense Function-Y5iFxWRTw1c.mp4 7.8 MBPart 02-Module 01-Lesson 06_Bayes' Rule/15. Equivalent Diagram-aUFWZ2uJuBE.mp4 7.7 MBPart 02-Module 01-Lesson 11_Robot Localization/10. Normalize Distribution-SW_wvez0izo.mp4 7.7 MBPart 06-Module 01-Lesson 03_The Search Problem/24. A Search-HNdOFYCtfu4.mp4 7.6 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/15. Separated Gaussians 2-edcfMK_bKXw.mp4 7.5 MBPart 02-Module 01-Lesson 08_Probability Distributions/10. Landing Probability-PNiaE1fy-7k.mp4 7.5 MBPart 02-Module 01-Lesson 06_Bayes' Rule/25. Disease Test 6-OdVAt79eQak.mp4 7.4 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/08. Measurement and Motion 1-Y7Mr_5Hfe24.mp4 7.4 MBPart 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/09. Nd113 C6 L1 09 L Interpreting Position Vs Time Graphs V3-NAEasXHN_PU.mp4 7.3 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/20. Kalman Prediction-tSfmiuB9s2c.mp4 7.3 MBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/02. Kalman Prediction-tSfmiuB9s2c.mp4 7.3 MBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/09. Nd113 C2 L3 08 L Look At Where We Are V2-5EjWMSV-0wo.mp4 7.3 MBPart 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/11. Defining The Derivative-043a3JRE1hU.mp4 7.2 MBPart 02-Module 01-Lesson 08_Probability Distributions/03. Intro To Probability Distribution 2-PglBg4eb_5M.mp4 7.2 MBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/10. Rate Gyros-TmnecSf80b0.mp4 7.2 MBPart 06-Module 01-Lesson 01_How to Solve Problems/10. How Are Inputs Represented-kG94A6xHqZk.mp4 7.1 MBPart 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/01. L3 01 V2-a_eHxfy5tnI.mp4 7.1 MBPart 02-Module 01-Lesson 06_Bayes' Rule/17. Probability Given Test-omC0zbJyzUY.mp4 7.0 MBPart 06-Module 01-Lesson 03_The Search Problem/35. A Note On Implementation-P3mkDcB-nqY.mp4 7.0 MBPart 02-Module 01-Lesson 04_Conditional Probability/12. Medical Example 3-Iz4ViIg9ZlQ.mp4 6.9 MBPart 06-Module 01-Lesson 03_The Search Problem/03. What Is A Problem-gepUYmWERZA.mp4 6.9 MBPart 06-Module 01-Lesson 01_How to Solve Problems/20. Different Approach-czjMsAXjWVg.mp4 6.9 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/45. Nd113 C7 45 L Classification V1-LWD1M2vqXXo.mp4 6.9 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/16. New Mean and Variance-SwxRWZaC1FM.mp4 6.6 MBPart 02-Module 01-Lesson 06_Bayes' Rule/35. Generalizing-SdMk3aROgSc.mp4 6.6 MBPart 06-Module 01-Lesson 01_How to Solve Problems/03. Como Resolver Problemas-E6t0oGRXXh8.mp4 6.6 MBPart 02-Module 01-Lesson 08_Probability Distributions/18. Birth Time Density-EhLR8l5XAiQ.mp4 6.5 MBPart 02-Module 01-Lesson 11_Robot Localization/16. Multiple Measurements--3qTapGGa-8.mp4 6.5 MBPart 01-Module 02-Lesson 02_Get Ready/03. Intro to Self-Driving Cars Intro To Jupyter Notebooks-0-5VG9FsdQ0.mp4 6.5 MBPart 06-Module 01-Lesson 01_How to Solve Problems/07. Understanding a Problem-hkspB2e0S9A.mp4 6.5 MBPart 02-Module 01-Lesson 08_Probability Distributions/20. Changing Density 2-v30w4s2djfc.mp4 6.5 MBPart 04-Module 01-Lesson 01_C++ Getting Started/15. Two Functions Same Name-0ZF649G58l4.mp4 6.4 MBPart 02-Module 01-Lesson 11_Robot Localization/37. Two Coin Quiz-2PZHPjyYnMg.mp4 6.4 MBPart 03-Module 01-Lesson 03_State and Object-Oriented Programming/17. Nd113 C2 L3 20 L Adding Color V2-iltQBIpbCSw.mp4 6.4 MBPart 06-Module 01-Lesson 01_How to Solve Problems/11. What Are the Outputs-5vjhu_cssNQ.mp4 6.3 MBPart 04-Module 01-Lesson 01_C++ Getting Started/01. Introduction-ahoiVrq4qAk.mp4 6.3 MBPart 06-Module 01-Lesson 02_Data Structures/01. Nd113 C5 L2 01 L Lesson Overview V1-LLrp9jq381k.mp4 6.3 MBPart 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/12. Solving Trig Problems Part1-qI4i845d7Qg.mp4 6.3 MBPart 06-Module 01-Lesson 03_The Search Problem/02. Welcome to Search!-pHySYq-wghU.mp4 6.3 MBPart 06-Module 01-Lesson 01_How to Solve Problems/33. Best Strategy-2T1JONL0WyE.mp4 6.2 MBPart 08-Module 01-Lesson 01_Computer Vision and Classification/24. Color Spaces and Transforms-qd49BIci-yw.mp4 6.2 MBPart 04-Module 01-Lesson 01_C++ Getting Started/02. Nd113 C3 L1 04 L Lesson Overview 2 V1-DjT2E23xhj8.mp4 6.1 MBPart 02-Module 01-Lesson 03_Probability/07. Fair Coin-9LrlrexpW_o.mp4 6.1 MBPart 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/03. L1 02 B V2-AFuQ1i3eUN8.mp4 6.1 MBPart 06-Module 01-Lesson 01_How to Solve Problems/23. What Should We Write First-YCQWVwsCZCk.mp4 6.1 MBPart 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/15. Conclusion-gMbDqd4ItiU.mp4 6.0 MBPart 02-Module 01-Lesson 03_Probability/23. Even Roll-DrnAR4SqlEE.mp4 6.0 MBPart 02-Module 01-Lesson 02_Joy Ride/01. Project Overview-Ij45-DpGejE.mp4 6.0 MBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/06. Nd113 C6 07 L The Integral Area Under A Curve H1 V2-Nhpvh2dolcE.mp4 6.0 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/11. Predicting the Peak-zc_GQiISQ3E.mp4 5.9 MBPart 06-Module 01-Lesson 01_How to Solve Problems/15. Take the Next Step-L4vB8eu6Wo8.mp4 5.8 MBPart 02-Module 01-Lesson 06_Bayes' Rule/29. Robot Sensing 3-m1LSU9SPZ2k.mp4 5.8 MBPart 02-Module 01-Lesson 08_Probability Distributions/12. Stops Nowhere-BlC2BwoDxL8.mp4 5.8 MBPart 02-Module 01-Lesson 03_Probability/05. Probability-arJxFjaMsBM.mp4 5.8 MBPart 02-Module 01-Lesson 03_Probability/22. One Of Three 2-gGgqTGZ9TKg.mp4 5.8 MBPart 06-Module 01-Lesson 02_Data Structures/03. 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State Vector-st26ov_TVwM.mp4 5.4 MBPart 03-Module 01-Lesson 03_State and Object-Oriented Programming/11. Car Object-SnfhGZ76h7Y.mp4 5.4 MBPart 06-Module 01-Lesson 01_How to Solve Problems/26. What Should We Do Next-ZETmw5tFcFU.mp4 5.3 MBPart 06-Module 01-Lesson 01_How to Solve Problems/19. Should We Implement It-M62yGhjmJoA.mp4 5.3 MBPart 06-Module 01-Lesson 01_How to Solve Problems/27. Define daysBetweenDates-oM3oyyQKQFU.mp4 5.3 MBPart 03-Module 01-Lesson 03_State and Object-Oriented Programming/07. Quantifying State-9zMbwSqTZAc.mp4 5.3 MBPart 02-Module 01-Lesson 08_Probability Distributions/19. Changing Density-tpsUlBbz5Jo.mp4 5.2 MBPart 06-Module 01-Lesson 01_How to Solve Problems/11. What Are the Outputs-4jNzxstbCy0.mp4 5.2 MBPart 02-Module 01-Lesson 08_Probability Distributions/22. Calculate Density-0gcTEExMH3k.mp4 5.2 MBPart 02-Module 01-Lesson 03_Probability/12. Probability In Robotics-BKLwvL1D0yE.mp4 5.1 MBPart 02-Module 01-Lesson 04_Conditional Probability/22. Two Coins 4-cDub-OOrIRE.mp4 5.0 MBPart 02-Module 01-Lesson 11_Robot Localization/36. Coin Flip Quiz-hzDsYZ61D5M.mp4 4.9 MBPart 06-Module 01-Lesson 03_The Search Problem/18. 17 - Uniform Cost Search 5-oiJLwSnrEDA.mp4 4.9 MBPart 06-Module 01-Lesson 01_How to Solve Problems/19. Should We Implement It-osHXLCQ9TKE.mp4 4.9 MBPart 02-Module 01-Lesson 03_Probability/06. Flipping Coins-lgUDXtUyLLg.mp4 4.8 MBPart 02-Module 01-Lesson 04_Conditional Probability/19. Two Coins 1-QIQBb4nLsHc.mp4 4.8 MBPart 06-Module 01-Lesson 03_The Search Problem/34. Problems With Search-5RmTKsNoG6M.mp4 4.8 MBPart 06-Module 01-Lesson 01_How to Solve Problems/14. The Expected Output-tiAFliSz9CY.mp4 4.8 MBPart 02-Module 01-Lesson 04_Conditional Probability/20. Two Coins 2-tI0J14yQr1s.mp4 4.7 MBPart 02-Module 01-Lesson 03_Probability/11. Complementary Outcomes-YseJqD-1oUg.mp4 4.7 MBPart 02-Module 01-Lesson 10_Gaussian Distributions/01. 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Multiple Measurements-gDO4sF8gR9k.mp4 4.3 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/14. Separated Gaussians-QAqsIWVVX0Y.mp4 4.3 MBPart 06-Module 01-Lesson 03_The Search Problem/12. Breath First Search 5-eyN4162UjH8.mp4 4.3 MBPart 06-Module 01-Lesson 03_The Search Problem/17. Uniform Cost Search 4-yO_uxVtEjq8.mp4 4.3 MBPart 03-Module 01-Lesson 03_State and Object-Oriented Programming/01. Localization Steps-4SiMoSTf4rQ.mp4 4.3 MBPart 02-Module 01-Lesson 03_Probability/13. Two Flips 1-1txkcmxk3vU.mp4 4.2 MBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/04. Variance Comparison-TGdMG81hXc8.mp4 4.1 MBPart 02-Module 01-Lesson 03_Probability/23. Even Roll-M3L0a5V4Nf0.mp4 4.1 MBPart 06-Module 01-Lesson 01_How to Solve Problems/35. Finish daysBetweenDates--70lzVJyS8Y.mp4 4.1 MBPart 06-Module 01-Lesson 01_How to Solve Problems/01. Nd113 Navigating L1 01 V1-5tdMvdcUF-E.mp4 4.1 MBPart 02-Module 01-Lesson 08_Probability Distributions/17. Density-4Ri4nhHKtU0.mp4 4.1 MBPart 02-Module 01-Lesson 05_Programming Probability in Python/01. Learn by Doing-ypPeggeRdTE.mp4 4.1 MBPart 02-Module 01-Lesson 11_Robot Localization/30. Formal Definition of Probability 1--F2gJXWbN6s.mp4 4.1 MBPart 02-Module 01-Lesson 11_Robot Localization/07. Generalized Uniform Distribution-nsSvTTA0p8E.mp4 4.0 MBPart 06-Module 01-Lesson 01_How to Solve Problems/12. Obey the Rules-NZq4vDooURs.mp4 4.0 MBPart 02-Module 01-Lesson 11_Robot Localization/01. About This Lesson-xEBSzD-fwps.mp4 4.0 MBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/11. Nd113 C2 L3 09 L Simplifying The Kalman Filter Equations V3-UpC0D-SEtD0.mp4 4.0 MBPart 02-Module 01-Lesson 06_Bayes' Rule/07. Bayes Rules-CohZnkZMOxE.mp4 4.0 MBPart 06-Module 01-Lesson 03_The Search Problem/14. Uniform Cost Search 1-nBdlU4jIDqU.mp4 4.0 MBPart 06-Module 01-Lesson 03_The Search Problem/15. 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Always Moving-EQBQlHvxAQA.mp4 3.8 MBPart 02-Module 01-Lesson 03_Probability/24. Doubles-On_Guw8wac8.mp4 3.8 MBPart 06-Module 01-Lesson 01_How to Solve Problems/39. Solution Step IV-H1oVKsgSsi0.mp4 3.8 MBPart 02-Module 01-Lesson 06_Bayes' Rule/20. Disease Test 1-qDGSvvabN18.mp4 3.8 MBPart 02-Module 01-Lesson 06_Bayes' Rule/24. Disease Test 5-nUxwwMNKIYo.mp4 3.8 MBPart 05-Module 01-Lesson 01_C++ Intro to Optimization/10. 04 L C And RAM V1 RENDER V1-60jEbKV1UOI.mp4 3.8 MBPart 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-qa9B4r5m8wM.mp4 3.8 MBPart 06-Module 01-Lesson 03_The Search Problem/07. Graph Search -A8GjRaPJQ5E.mp4 3.7 MBPart 02-Module 01-Lesson 11_Robot Localization/17. Exact Motion-Iky7rJXQU_4.mp4 3.7 MBPart 06-Module 01-Lesson 03_The Search Problem/21. Search Comparison 2-Fh5b8xVJhR8.mp4 3.7 MBPart 01-Module 02-Lesson 01_The Carla Chronicles Back on Track/img/udacity-page-3-shades-1.jpg 3.7 MBPart 02-Module 01-Lesson 04_Conditional Probability/17. 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Two Coins 2-hoVOT8qcQ7c.th.vtt 3.3 kBPart 02-Module 01-Lesson 06_Bayes' Rule/09. Prior And Posterior-o2Tpws5C2Eg.pt-BR.vtt 3.3 kBPart 06-Module 01-Lesson 01_How to Solve Problems/36. Solution Step I-bIZgt0ttMeU.en.vtt 3.3 kBPart 06-Module 01-Lesson 01_How to Solve Problems/18. Algorithm Pseudocode-Ei91QeYiG_E.ja.vtt 3.3 kBPart 06-Module 01-Lesson 01_How to Solve Problems/09. What Are the Inputs-cAr-unfe-mg.en.vtt 3.3 kBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/08. Kalman Filter Design-KYEr4BXhD_E.zh-CN.vtt 3.3 kBPart 03-Module 01-Lesson 03_State and Object-Oriented Programming/09. Always Moving-EQBQlHvxAQA.en.vtt 3.3 kBPart 02-Module 01-Lesson 11_Robot Localization/03. Localization-31xZhj2uPr4.es-ES.vtt 3.3 kBPart 02-Module 01-Lesson 11_Robot Localization/03. Localization-31xZhj2uPr4.es.vtt 3.3 kBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/03. Kalman Filter Land-LXJ5jrvDuEk.ja.vtt 3.2 kBPart 02-Module 01-Lesson 11_Robot Localization/03. Localization-31xZhj2uPr4.pt-PT.vtt 3.2 kBPart 02-Module 01-Lesson 11_Robot Localization/03. Localization-31xZhj2uPr4.pt.vtt 3.2 kBPart 02-Module 01-Lesson 06_Bayes' Rule/26. Bayes Rule Summary-RgXQ8GRsjfc.pt-BR.vtt 3.2 kBPart 02-Module 01-Lesson 04_Conditional Probability/11. Medical Example 2-FV_hc3MzS_8.pt-BR.vtt 3.2 kBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/07. Approximating The Integral-9C05AHzI_I8.zh-CN.vtt 3.2 kBPart 02-Module 01-Lesson 11_Robot Localization/03. Localization-31xZhj2uPr4.it.vtt 3.2 kBPart 06-Module 01-Lesson 03_The Search Problem/06. Tree Search Continued-8yID2dTeBSM.zh-CN.vtt 3.2 kBPart 02-Module 01-Lesson 11_Robot Localization/03. Localization-31xZhj2uPr4.pl.vtt 3.2 kBPart 02-Module 01-Lesson 11_Robot Localization/03. Localization-31xZhj2uPr4.ja.vtt 3.2 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/03. Gaussian Intro-GHKKUR6tZE0.es-ES.vtt 3.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/18. Algorithm Pseudocode-Ei91QeYiG_E.en.vtt 3.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/36. Solution Step I-bIZgt0ttMeU.zh-CN.vtt 3.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/08. Cancer Test-CNpSrdnYvbo.zh-CN.vtt 3.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/08. Cancer Test-CNpSrdnYvbo.pt-BR.vtt 3.1 kBPart 06-Module 01-Lesson 03_The Search Problem/24. A Search-HNdOFYCtfu4.zh-CN.vtt 3.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/30. Step Three daysBetweenDates-DOkkOsraobw.ja.vtt 3.1 kBPart 02-Module 01-Lesson 11_Robot Localization/03. Localization-31xZhj2uPr4.zh-CN.vtt 3.1 kBPart 06-Module 01-Lesson 03_The Search Problem/18. 17 - Uniform Cost Search 5-oiJLwSnrEDA.en.vtt 3.1 kBPart 02-Module 01-Lesson 04_Conditional Probability/11. Medical Example 2-FV_hc3MzS_8.it.vtt 3.1 kBPart 02-Module 01-Lesson 04_Conditional Probability/11. Medical Example 2-FV_hc3MzS_8.es-ES.vtt 3.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/09. Prior And Posterior-o2Tpws5C2Eg.zh-CN.vtt 3.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/30. Robot Sensing 4-vasdN2Gol0M.th.vtt 3.0 kBPart 05-Module 01-Lesson 01_C++ Intro to Optimization/02. C Opt 01 L V2-Kdx1_BI5ddc.zh-CN.vtt 3.0 kBPart 06-Module 01-Lesson 01_How to Solve Problems/19. Should We Implement It-osHXLCQ9TKE.zh-CN.vtt 3.0 kBPart 06-Module 01-Lesson 01_How to Solve Problems/09. What Are the Inputs-cAr-unfe-mg.zh-CN.vtt 3.0 kBPart 02-Module 01-Lesson 11_Robot Localization/26. Sense and Move-K8g3Hss8Q1A.es-ES.vtt 3.0 kBPart 02-Module 01-Lesson 11_Robot Localization/03. Localization-31xZhj2uPr4.en.vtt 3.0 kBPart 03-Module 01-Lesson 03_State and Object-Oriented Programming/01. Localization Steps-4SiMoSTf4rQ.en.vtt 3.0 kBPart 02-Module 01-Lesson 11_Robot Localization/35. Theorem of Total Probability-byZ-BzbQA5M.es-ES.vtt 3.0 kBPart 06-Module 01-Lesson 03_The Search Problem/04. Example Route Finding-5lrkPKQwOFE.en.vtt 3.0 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/03. Gaussian Intro-GHKKUR6tZE0.en.vtt 3.0 kBPart 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/11. Defining The Derivative-043a3JRE1hU.zh-CN.vtt 3.0 kBPart 08-Module 01-Lesson 01_Computer Vision and Classification/37. Nd113 C7 33 L Features And Classification-Ni3ocWoUDPk.zh-CN.vtt 3.0 kBPart 06-Module 01-Lesson 03_The Search Problem/35. A Note On Implementation-P3mkDcB-nqY.en.vtt 3.0 kBPart 02-Module 01-Lesson 06_Bayes' Rule/27. Robot Sensing 1-_DjfTytro6I.th.vtt 3.0 kBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/06. 07 L The Integral Area Under A Curve H1 V2-QNvgwoIrsIE.zh-CN.vtt 3.0 kBPart 06-Module 01-Lesson 03_The Search Problem/18. 17 - Uniform Cost Search 5-oiJLwSnrEDA.zh-CN.vtt 3.0 kBPart 08-Module 01-Lesson 01_Computer Vision and Classification/15. Color Images--XbXiiGQ9gw.en.vtt 3.0 kBPart 06-Module 01-Lesson 01_How to Solve Problems/36. Solution Step I-bIZgt0ttMeU.pt-BR.vtt 3.0 kBPart 06-Module 01-Lesson 03_The Search Problem/04. Example Route Finding-5lrkPKQwOFE.zh-CN.vtt 2.9 kBPart 02-Module 01-Lesson 04_Conditional Probability/23. Summary-yepMH9VswI8.it.vtt 2.9 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/03. Gaussian Intro-GHKKUR6tZE0.ja.vtt 2.9 kBPart 02-Module 01-Lesson 06_Bayes' Rule/09. Prior And Posterior-o2Tpws5C2Eg.ja.vtt 2.9 kBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/05. 06 L Reasoning About Two Peaks H1 V1-bgPS1GO1EJs.en.vtt 2.9 kBPart 04-Module 01-Lesson 01_C++ Getting Started/15. Two Functions Same Name-9SgmzOfBmRU.en.vtt 2.9 kBPart 02-Module 01-Lesson 03_Probability/06. Flipping Coins-OpNufHYgJCg.th.vtt 2.9 kBPart 02-Module 01-Lesson 04_Conditional Probability/23. Summary-yepMH9VswI8.es-ES.vtt 2.9 kBPart 02-Module 01-Lesson 04_Conditional Probability/11. Medical Example 2-FV_hc3MzS_8.en.vtt 2.9 kBPart 02-Module 01-Lesson 11_Robot Localization/27. Sense and Move 2-rmWL_3r8MKo.pt-PT.vtt 2.9 kBPart 02-Module 01-Lesson 11_Robot Localization/27. Sense and Move 2-rmWL_3r8MKo.pt.vtt 2.9 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/10. Shifting the Mean-8c479K2UCZo.ru.vtt 2.9 kBPart 02-Module 01-Lesson 11_Robot Localization/08. Probability After Sense-UFcTLCttNRI.ru.vtt 2.9 kBPart 02-Module 01-Lesson 11_Robot Localization/27. Sense and Move 2-rmWL_3r8MKo.es-ES.vtt 2.9 kBPart 06-Module 01-Lesson 01_How to Solve Problems/30. Step Three daysBetweenDates-DOkkOsraobw.en.vtt 2.9 kBPart 02-Module 01-Lesson 11_Robot Localization/26. Sense and Move-K8g3Hss8Q1A.it.vtt 2.9 kBPart 02-Module 01-Lesson 11_Robot Localization/26. Sense and Move-K8g3Hss8Q1A.ja.vtt 2.8 kBPart 06-Module 01-Lesson 01_How to Solve Problems/28. Step One Pseudocode-hJzpU5qC3hs.ar.vtt 2.8 kBPart 06-Module 01-Lesson 01_How to Solve Problems/09. What Are the Inputs-cAr-unfe-mg.pt-BR.vtt 2.8 kBPart 03-Module 01-Lesson 03_State and Object-Oriented Programming/09. Always Moving-EQBQlHvxAQA.zh-CN.vtt 2.8 kBPart 06-Module 01-Lesson 01_How to Solve Problems/14. The Expected Output-trokjJravhc.ar.vtt 2.8 kBPart 02-Module 01-Lesson 11_Robot Localization/26. Sense and Move-K8g3Hss8Q1A.pt-PT.vtt 2.8 kBPart 02-Module 01-Lesson 11_Robot Localization/26. Sense and Move-K8g3Hss8Q1A.pt.vtt 2.8 kBPart 04-Module 01-Lesson 01_C++ Getting Started/06. Static Vs Dynamic Typing-D7v6iIAORkE.en.vtt 2.8 kBPart 02-Module 01-Lesson 08_Probability Distributions/03. Intro To Probability Distribution 2-PglBg4eb_5M.en.vtt 2.8 kBPart 02-Module 01-Lesson 04_Conditional Probability/11. Medical Example 2-FV_hc3MzS_8.ja.vtt 2.8 kBPart 02-Module 01-Lesson 03_Probability/21. One Of Three 1-bDCXSxkochE.th.vtt 2.8 kBPart 02-Module 01-Lesson 11_Robot Localization/35. Theorem of Total Probability-byZ-BzbQA5M.pt-PT.vtt 2.8 kBPart 02-Module 01-Lesson 11_Robot Localization/35. Theorem of Total Probability-byZ-BzbQA5M.it.vtt 2.8 kBPart 02-Module 01-Lesson 11_Robot Localization/35. Theorem of Total Probability-byZ-BzbQA5M.pt.vtt 2.8 kBPart 06-Module 01-Lesson 01_How to Solve Problems/18. Algorithm Pseudocode-Ei91QeYiG_E.zh-CN.vtt 2.8 kBPart 02-Module 01-Lesson 11_Robot Localization/27. Sense and Move 2-rmWL_3r8MKo.it.vtt 2.8 kBPart 06-Module 01-Lesson 01_How to Solve Problems/19. Should We Implement It-osHXLCQ9TKE.pt-BR.vtt 2.8 kBPart 02-Module 01-Lesson 11_Robot Localization/26. Sense and Move-K8g3Hss8Q1A.en.vtt 2.8 kBPart 06-Module 01-Lesson 01_How to Solve Problems/18. Algorithm Pseudocode-Ei91QeYiG_E.pt-BR.vtt 2.8 kBPart 03-Module 01-Lesson 03_State and Object-Oriented Programming/01. Localization Steps-4SiMoSTf4rQ.zh-CN.vtt 2.8 kBPart 02-Module 01-Lesson 06_Bayes' Rule/26. Bayes Rule Summary-RgXQ8GRsjfc.es-ES.vtt 2.7 kBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/10. Nd113 C2 L3 08 L The Kalman Filter Equations V2-X9UUpk5URuw.en.vtt 2.7 kBPart 06-Module 01-Lesson 01_How to Solve Problems/30. Step Three daysBetweenDates-DOkkOsraobw.zh-CN.vtt 2.7 kBPart 04-Module 01-Lesson 01_C++ Getting Started/04. Why C++-_t4ZvwfnuCA.en.vtt 2.7 kBPart 02-Module 01-Lesson 11_Robot Localization/35. Theorem of Total Probability-byZ-BzbQA5M.en.vtt 2.7 kBPart 02-Module 01-Lesson 04_Conditional Probability/23. Summary-yepMH9VswI8.en.vtt 2.7 kBPart 06-Module 01-Lesson 01_How to Solve Problems/04. Days Between Dates-VLrJ01wEajw.ja.vtt 2.7 kBPart 04-Module 01-Lesson 01_C++ Getting Started/15. Two Functions Same Name-9SgmzOfBmRU.zh-CN.vtt 2.7 kBPart 06-Module 01-Lesson 03_The Search Problem/21. Search Comparison 2-Fh5b8xVJhR8.en.vtt 2.7 kBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/06. Nd113 C6 07 L The Integral Area Under A Curve H1 V2-Nhpvh2dolcE.en.vtt 2.7 kBPart 02-Module 01-Lesson 06_Bayes' Rule/26. Bayes Rule Summary-RgXQ8GRsjfc.ja.vtt 2.7 kBPart 02-Module 01-Lesson 11_Robot Localization/27. Sense and Move 2-rmWL_3r8MKo.ja.vtt 2.7 kBPart 08-Module 01-Lesson 01_Computer Vision and Classification/18. Pre-processing--h1GS0SEyzY.en.vtt 2.7 kBPart 02-Module 01-Lesson 11_Robot Localization/35. Theorem of Total Probability-byZ-BzbQA5M.ja.vtt 2.7 kBPart 06-Module 01-Lesson 01_How to Solve Problems/23. What Should We Write First-HRepefDqkDM.es-AR.vtt 2.7 kBPart 06-Module 01-Lesson 03_The Search Problem/35. A Note On Implementation-P3mkDcB-nqY.zh-CN.vtt 2.7 kBPart 02-Module 01-Lesson 11_Robot Localization/23. Limit Distribution Quiz-SXSafquSoW8.es-ES.vtt 2.7 kBPart 04-Module 01-Lesson 01_C++ Getting Started/16. Function Signatures 1-T6kQ_4w98IQ.en.vtt 2.7 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/03. Gaussian Intro-GHKKUR6tZE0.zh-CN.vtt 2.7 kBPart 06-Module 01-Lesson 01_How to Solve Problems/22. Don't Optimize Prematurely-uQDk8euwyDI.ar.vtt 2.7 kBPart 02-Module 01-Lesson 11_Robot Localization/27. Sense and Move 2-rmWL_3r8MKo.en.vtt 2.6 kBPart 02-Module 01-Lesson 06_Bayes' Rule/26. Bayes Rule Summary-RgXQ8GRsjfc.en.vtt 2.6 kBPart 02-Module 01-Lesson 11_Robot Localization/23. Limit Distribution Quiz-SXSafquSoW8.pt-PT.vtt 2.6 kBPart 02-Module 01-Lesson 11_Robot Localization/23. Limit Distribution Quiz-SXSafquSoW8.pt.vtt 2.6 kBPart 02-Module 01-Lesson 03_Probability/24. Doubles-fkUyTJNbdzU.th.vtt 2.6 kBPart 02-Module 01-Lesson 11_Robot Localization/26. Sense and Move-K8g3Hss8Q1A.zh-CN.vtt 2.6 kBPart 06-Module 01-Lesson 01_How to Solve Problems/06. First Step-N8dKtrrCZ7U.ja.vtt 2.6 kBPart 02-Module 01-Lesson 11_Robot Localization/23. Limit Distribution Quiz-SXSafquSoW8.ja.vtt 2.6 kBPart 04-Module 01-Lesson 01_C++ Getting Started/06. Static Vs Dynamic Typing-D7v6iIAORkE.zh-CN.vtt 2.6 kBPart 02-Module 01-Lesson 11_Robot Localization/23. Limit Distribution Quiz-SXSafquSoW8.it.vtt 2.6 kBPart 03-Module 01-Lesson 03_State and Object-Oriented Programming/03. Motion Models-qSdbn_PVQnk.en.vtt 2.6 kBPart 08-Module 01-Lesson 01_Computer Vision and Classification/15. Color Images--XbXiiGQ9gw.zh-CN.vtt 2.5 kBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/03. Nd113 C6 L2 03 L Acceleration Basics V2-ea6b4PZ7YXU.en.vtt 2.5 kBPart 02-Module 01-Lesson 04_Conditional Probability/18. Total Probability-YSYpzFR4k1I.ar.vtt 2.5 kBPart 02-Module 01-Lesson 04_Conditional Probability/21. Two Coins 3-JIWv5fU3GLA.ar.vtt 2.5 kBPart 06-Module 01-Lesson 03_The Search Problem/34. Problems With Search-5RmTKsNoG6M.en.vtt 2.5 kBPart 02-Module 01-Lesson 11_Robot Localization/19. Inexact Motion 1-C3f-T9_GTpw.ja.vtt 2.5 kBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/03. Kalman Filter Land-LXJ5jrvDuEk.zh-CN.vtt 2.5 kBPart 06-Module 01-Lesson 01_How to Solve Problems/30. Step Three daysBetweenDates-DOkkOsraobw.pt-BR.vtt 2.5 kBPart 08-Module 01-Lesson 01_Computer Vision and Classification/02. Computer Vision and Sebastian-pil3PeZzCIY.en.vtt 2.5 kBPart 06-Module 01-Lesson 01_How to Solve Problems/24. Define Simple nextDay-Qttkfhh3I5s.es-MX.vtt 2.5 kBPart 02-Module 01-Lesson 11_Robot Localization/35. Theorem of Total Probability-byZ-BzbQA5M.zh-CN.vtt 2.5 kBPart 02-Module 01-Lesson 11_Robot Localization/23. Limit Distribution Quiz-SXSafquSoW8.en.vtt 2.5 kBPart 06-Module 01-Lesson 01_How to Solve Problems/37. Solution Step II-SGC8UAz12Q4.ja.vtt 2.5 kBPart 04-Module 01-Lesson 01_C++ Getting Started/16. Function Signatures 1-T6kQ_4w98IQ.zh-CN.vtt 2.5 kBPart 02-Module 01-Lesson 11_Robot Localization/27. Sense and Move 2-rmWL_3r8MKo.zh-CN.vtt 2.5 kBPart 06-Module 01-Lesson 03_The Search Problem/21. Search Comparison 2-Fh5b8xVJhR8.zh-CN.vtt 2.5 kBPart 06-Module 01-Lesson 01_How to Solve Problems/14. The Expected Output-trokjJravhc.ja.vtt 2.5 kBPart 02-Module 01-Lesson 04_Conditional Probability/23. Summary-yepMH9VswI8.pt-BR.vtt 2.5 kBPart 06-Module 01-Lesson 01_How to Solve Problems/23. What Should We Write First-HRepefDqkDM.en.vtt 2.5 kBPart 02-Module 01-Lesson 04_Conditional Probability/23. Summary-yepMH9VswI8.zh-CN.vtt 2.5 kBPart 06-Module 01-Lesson 01_How to Solve Problems/04. Days Between Dates-VLrJ01wEajw.en.vtt 2.5 kBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/05. 06 L Reasoning About Two Peaks H1 V1-bgPS1GO1EJs.zh-CN.vtt 2.5 kBPart 02-Module 01-Lesson 04_Conditional Probability/11. Medical Example 2-FV_hc3MzS_8.zh-CN.vtt 2.5 kBPart 02-Module 01-Lesson 06_Bayes' Rule/14. Bayes Rule Diagram-b8M9CWxRyQ4.ar.vtt 2.5 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/12. Parameter Update-d8UrbKKlGxI.es-ES.vtt 2.5 kBPart 04-Module 01-Lesson 01_C++ Getting Started/04. Why C++-_t4ZvwfnuCA.zh-CN.vtt 2.5 kBPart 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/06. Delta X Over Delta T-AsBTLDf0vQs.en.vtt 2.5 kBPart 06-Module 01-Lesson 03_The Search Problem/31. Sliding Blocks Puzzle-Dzah_49isp8.en.vtt 2.5 kBPart 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/12. Solving Trig Problems Part1-qI4i845d7Qg.en.vtt 2.4 kBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/10. Nd113 C2 L3 08 L The Kalman Filter Equations V2-X9UUpk5URuw.zh-CN.vtt 2.4 kBPart 02-Module 01-Lesson 08_Probability Distributions/03. Intro To Probability Distribution 2-PglBg4eb_5M.zh-CN.vtt 2.4 kBPart 02-Module 01-Lesson 04_Conditional Probability/23. Summary-yepMH9VswI8.ja.vtt 2.4 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/12. Parameter Update-d8UrbKKlGxI.ja.vtt 2.4 kBPart 05-Module 01-Lesson 01_C++ Intro to Optimization/12. 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Understanding a Problem-hkspB2e0S9A.en.vtt 1.2 kBPart 02-Module 01-Lesson 11_Robot Localization/37. Two Coin Quiz-2PZHPjyYnMg.es-ES.vtt 1.2 kBPart 02-Module 01-Lesson 06_Bayes' Rule/19. Normalizing Probability-yYqN9Mf4jqw.ja.vtt 1.2 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/04. Variance Comparison-rczAG7meAY4.en.vtt 1.2 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/08. Measurement and Motion 1-Y7Mr_5Hfe24.es-ES.vtt 1.2 kBPart 06-Module 01-Lesson 01_How to Solve Problems/11. What Are the Outputs-5vjhu_cssNQ.zh-CN.vtt 1.2 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/04. Variance Comparison-rczAG7meAY4.es-ES.vtt 1.2 kBPart 02-Module 01-Lesson 06_Bayes' Rule/20. Disease Test 1-05upwXtARuo.th.vtt 1.2 kBPart 06-Module 01-Lesson 01_How to Solve Problems/01. Nd113 Navigating L1 01 V1-5tdMvdcUF-E.zh-CN.vtt 1.2 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/20. Kalman Prediction-tSfmiuB9s2c.zh-CN.vtt 1.2 kBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/02. Kalman Prediction-tSfmiuB9s2c.zh-CN.vtt 1.2 kBPart 02-Module 01-Lesson 11_Robot Localization/20. Inexact Motion 2-jR7FERpsqe4.it.vtt 1.2 kBPart 05-Module 01-Lesson 01_C++ Intro to Optimization/01. Course Introduction-Lwc5oYApdUM.zh-CN.vtt 1.2 kBPart 02-Module 01-Lesson 04_Conditional Probability/12. Medical Example 3-Iz4ViIg9ZlQ.pt-BR.vtt 1.2 kBPart 02-Module 01-Lesson 08_Probability Distributions/22. Calculate Density-oZDLtTdhDy4.en.vtt 1.2 kBPart 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/15. Conclusion-gMbDqd4ItiU.en.vtt 1.2 kBPart 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/01. L3 01 V2-a_eHxfy5tnI.en.vtt 1.2 kBPart 02-Module 01-Lesson 03_Probability/06. Flipping Coins-lgUDXtUyLLg.th.vtt 1.2 kBPart 02-Module 01-Lesson 11_Robot Localization/36. Coin Flip Quiz-ASUXN9Ay35M.it.vtt 1.2 kBPart 02-Module 01-Lesson 03_Probability/21. One Of Three 1-bDCXSxkochE.en.vtt 1.2 kBPart 06-Module 01-Lesson 01_How to Solve Problems/32. Real World Problem-lY0CYTfkLWo.zh-CN.vtt 1.2 kBPart 06-Module 01-Lesson 01_How to Solve Problems/26. What Should We Do Next-ZETmw5tFcFU.zh-CN.vtt 1.2 kBPart 02-Module 01-Lesson 11_Robot Localization/20. Inexact Motion 2-jR7FERpsqe4.zh-CN.vtt 1.2 kBPart 06-Module 01-Lesson 01_How to Solve Problems/20. Different Approach-czjMsAXjWVg.es-MX.vtt 1.2 kBPart 02-Module 01-Lesson 06_Bayes' Rule/15. Equivalent Diagram-aUFWZ2uJuBE.en.vtt 1.2 kBPart 02-Module 01-Lesson 06_Bayes' Rule/36. Sebastian At Home-TtmQ7YCw_1Y.es-ES.vtt 1.2 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/15. Separated Gaussians 2-edcfMK_bKXw.zh-CN.vtt 1.2 kBPart 02-Module 01-Lesson 06_Bayes' Rule/02. Bayes' Rule and Robotics-meNSO42JF6I.pt-BR.vtt 1.2 kBPart 02-Module 01-Lesson 03_Probability/01. Nd113 C1 L3 01 L Introducing Uncertainty V1-NDOm-0qN8e8.zh-CN.vtt 1.2 kBPart 06-Module 01-Lesson 01_How to Solve Problems/33. Best Strategy-2T1JONL0WyE.pt-BR.vtt 1.2 kBPart 02-Module 01-Lesson 06_Bayes' Rule/36. Sebastian At Home-TtmQ7YCw_1Y.ja.vtt 1.2 kBPart 02-Module 01-Lesson 03_Probability/21. One Of Three 1-bDCXSxkochE.ja.vtt 1.2 kBPart 06-Module 01-Lesson 01_How to Solve Problems/12. Obey the Rules-NZq4vDooURs.ar.vtt 1.2 kBPart 02-Module 01-Lesson 11_Robot Localization/20. Inexact Motion 2-jR7FERpsqe4.pt-PT.vtt 1.2 kBPart 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/07. Power of Trigonometry-yLMTfBq_I3k.zh-CN.vtt 1.2 kBPart 02-Module 01-Lesson 11_Robot Localization/20. Inexact Motion 2-jR7FERpsqe4.pt.vtt 1.2 kBPart 06-Module 01-Lesson 01_How to Solve Problems/40. Conclusion-JmP5wzHFchc.en.vtt 1.2 kBPart 06-Module 01-Lesson 03_The Search Problem/17. Uniform Cost Search 4-yO_uxVtEjq8.en.vtt 1.2 kBPart 02-Module 01-Lesson 03_Probability/21. One Of Three 1-bDCXSxkochE.hr.vtt 1.2 kBPart 06-Module 01-Lesson 01_How to Solve Problems/29. Step Two Helper Function-lpprz4op11k.ja.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/31. Test for Valid Inputs-7c7wYMftRSg.ja.vtt 1.1 kBPart 06-Module 01-Lesson 03_The Search Problem/17. Uniform Cost Search 4-yO_uxVtEjq8.zh-CN.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/36. Coin Flip Quiz-ASUXN9Ay35M.zh-CN.vtt 1.1 kBPart 03-Module 01-Lesson 05_Implement Matrix Class/01. Nd113P2 C2 L5 01 L Implement Matrix-0Ie9IxW9VDw.en.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/35. Finish daysBetweenDates--70lzVJyS8Y.ar.vtt 1.1 kBPart 02-Module 01-Lesson 04_Conditional Probability/21. Two Coins 3-GO6kbL3QRBE.it.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/15. Test Sense Function-Lf2DYUCsUH4.ja.vtt 1.1 kBPart 02-Module 01-Lesson 08_Probability Distributions/18. Birth Time Density-EhLR8l5XAiQ.es-ES.vtt 1.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/19. Normalizing Probability-yYqN9Mf4jqw.en.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/36. Coin Flip Quiz-ASUXN9Ay35M.en.vtt 1.1 kBPart 02-Module 01-Lesson 08_Probability Distributions/18. Birth Time Density-EhLR8l5XAiQ.en.vtt 1.1 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/16. New Mean and Variance-yo8jf0U4hlc.zh-CN.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/07. Understanding a Problem-hkspB2e0S9A.pt-BR.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/21. Simple Mechanical Algorithm-wN445aeFEFI.en.vtt 1.1 kBPart 02-Module 01-Lesson 04_Conditional Probability/21. Two Coins 3-GO6kbL3QRBE.es-ES.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/27. Define daysBetweenDates-oM3oyyQKQFU.en.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/16. Multiple Measurements--3qTapGGa-8.pt-PT.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/16. Multiple Measurements--3qTapGGa-8.pt.vtt 1.1 kBPart 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/08. Nd113 C6 L3 08 L Opposite Adjacent Hypotenuse V2-hJ-7qj9iHWo.zh-CN.vtt 1.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/28. Robot Sensing 2-aBBmlnd7okQ.ar.vtt 1.1 kBPart 02-Module 01-Lesson 04_Conditional Probability/22. Two Coins 4-9R44IyZ-aQI.ja.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/16. Multiple Measurements--3qTapGGa-8.es-ES.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/37. Two Coin Quiz-2PZHPjyYnMg.ja.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/16. Multiple Measurements--3qTapGGa-8.es.vtt 1.1 kBPart 02-Module 01-Lesson 03_Probability/07. Fair Coin-9LrlrexpW_o.ar.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/15. Take the Next Step-L4vB8eu6Wo8.zh-CN.vtt 1.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/11. Normalizing 2-WYA5Zbf8HC4.th.vtt 1.1 kBPart 07-Module 01-Lesson 02_Accelerometers, Rate Gyros and Integrals/10. Rate Gyros-TmnecSf80b0.zh-CN.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/29. Step Two Helper Function-lpprz4op11k.en.vtt 1.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/08. Cancer Test-FnNveASivMA.it.vtt 1.1 kBPart 02-Module 01-Lesson 03_Probability/19. One Head 1-T4A5uyqesjo.th.vtt 1.1 kBPart 07-Module 01-Lesson 01_Odometers, Speedometers and Derivatives/03. L1 02 B V2-AFuQ1i3eUN8.zh-CN.vtt 1.1 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/02. Tracking Intro-lDykH1UHq38.zh-CN.vtt 1.1 kBPart 03-Module 01-Lesson 05_Implement Matrix Class/01. Nd113P2 C2 L5 01 L Implement Matrix-0Ie9IxW9VDw.zh-CN.vtt 1.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/15. Equivalent Diagram-aUFWZ2uJuBE.ja.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/11. What Are the Outputs-4jNzxstbCy0.en.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/37. Two Coin Quiz-2PZHPjyYnMg.it.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/21. Simple Mechanical Algorithm-wN445aeFEFI.ja.vtt 1.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/25. Disease Test 6-OdVAt79eQak.ar.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/16. Multiple Measurements--3qTapGGa-8.it.vtt 1.1 kBPart 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/15. Conclusion-gMbDqd4ItiU.zh-CN.vtt 1.1 kBPart 02-Module 01-Lesson 08_Probability Distributions/02. Intro To Probability Distribution 1-gqPjMDVFvNg.en.vtt 1.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/08. Cancer Test-FnNveASivMA.es-ES.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/37. Two Coin Quiz-2PZHPjyYnMg.zh-CN.vtt 1.1 kBPart 02-Module 01-Lesson 03_Probability/03. Learning Objectives Explained-tAkq3iZLJ-c.zh-CN.vtt 1.1 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/08. Measurement and Motion 1-Y7Mr_5Hfe24.ja.vtt 1.1 kBPart 02-Module 01-Lesson 08_Probability Distributions/12. Stops Nowhere-BlC2BwoDxL8.es-ES.vtt 1.1 kBPart 02-Module 01-Lesson 03_Probability/09. Loaded Coin 2-dGffszQYzqc.ar.vtt 1.1 kBPart 02-Module 01-Lesson 04_Conditional Probability/04. Dependent Events and Conditional Probability-GDWdCH4ilDI.en.vtt 1.1 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/13. Parameter Update 2-_AAkw_fynwc.es-ES.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/40. Conclusion-JmP5wzHFchc.pt-BR.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/37. Two Coin Quiz-2PZHPjyYnMg.pt-PT.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/37. Two Coin Quiz-2PZHPjyYnMg.pt.vtt 1.1 kBPart 02-Module 01-Lesson 03_Probability/23. Even Roll-DrnAR4SqlEE.ar.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/11. What Are the Outputs-5vjhu_cssNQ.pt-BR.vtt 1.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/08. Cancer Test-FnNveASivMA.en.vtt 1.1 kBPart 02-Module 01-Lesson 04_Conditional Probability/12. Medical Example 3-Iz4ViIg9ZlQ.ja.vtt 1.1 kBPart 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/05. Nd113 C6 L3 05 L Moving At 53 Degrees V2-VmoknN6xLKs.zh-CN.vtt 1.1 kBPart 06-Module 01-Lesson 03_The Search Problem/22. Search Comparison 3-4KHmQEoqmeI.en.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/17. Exact Motion-1mL6CtD3rAM.es-MX.vtt 1.1 kBPart 02-Module 01-Lesson 03_Probability/12. Probability In Robotics-BKLwvL1D0yE.en.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/16. Multiple Measurements--3qTapGGa-8.ja.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/37. Two Coin Quiz-2PZHPjyYnMg.en.vtt 1.1 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/16. New Mean and Variance-SwxRWZaC1FM.ja.vtt 1.1 kBPart 02-Module 01-Lesson 08_Probability Distributions/20. Changing Density 2-v30w4s2djfc.es-ES.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/19. Should We Implement It-M62yGhjmJoA.zh-CN.vtt 1.1 kBPart 06-Module 01-Lesson 01_How to Solve Problems/20. Different Approach-czjMsAXjWVg.en.vtt 1.1 kBPart 02-Module 01-Lesson 04_Conditional Probability/20. Two Coins 2-tI0J14yQr1s.ar.vtt 1.1 kBPart 02-Module 01-Lesson 03_Probability/24. Doubles-On_Guw8wac8.th.vtt 1.1 kBPart 02-Module 01-Lesson 06_Bayes' Rule/36. Sebastian At Home-TtmQ7YCw_1Y.en.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/13. Sense Function-Y5iFxWRTw1c.es-ES.vtt 1.1 kBPart 03-Module 01-Lesson 04_Matrices and Transformation of State/01. Nd113 C2 L3 01 L Connection To Kalman Filters V1-bwaakDKn4nI.zh-CN.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/17. Exact Motion-1mL6CtD3rAM.es-ES.vtt 1.1 kBPart 02-Module 01-Lesson 04_Conditional Probability/21. Two Coins 3-GO6kbL3QRBE.en.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/13. Sense Function-Y5iFxWRTw1c.es.vtt 1.1 kBPart 03-Module 01-Lesson 01_Section Overview/01. Introduction to Matrices-Ugx3mldc0lE.en.vtt 1.1 kBPart 02-Module 01-Lesson 08_Probability Distributions/18. Birth Time Density-EhLR8l5XAiQ.ja.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/17. Exact Motion-1mL6CtD3rAM.es.vtt 1.1 kBPart 02-Module 01-Lesson 03_Probability/25. Summary-hIEDvyCETEw.zh-CN.vtt 1.1 kBPart 02-Module 01-Lesson 11_Robot Localization/16. Multiple Measurements--3qTapGGa-8.en.vtt 1.1 kBPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/08. Measurement and Motion 1-Y7Mr_5Hfe24.en.vtt 1.0 kBPart 07-Module 01-Lesson 03_Two Dimensional Robot Motion and Trigonometry/01. L3 01 V2-a_eHxfy5tnI.zh-CN.vtt 1.0 kBPart 02-Module 01-Lesson 11_Robot Localization/16. Multiple Measurements--3qTapGGa-8.zh-CN.vtt 1.0 kBPart 06-Module 01-Lesson 01_How to Solve Problems/07. Understanding a Problem-hkspB2e0S9A.zh-CN.vtt 1.0 kBPart 06-Module 01-Lesson 01_How to Solve Problems/32. 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Disease Test 6-cdFrLeXIkZU.zh-CN.vtt 214 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/30. Robot Sensing 4-d_fbDqAGVdE.en.vtt 214 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/22. Disease Test 3-a61GPGk-Qy4.en.vtt 214 BytesPart 02-Module 01-Lesson 11_Robot Localization/12. Sum of Probabilities-6c0XvswnGm0.it.vtt 213 BytesPart 02-Module 01-Lesson 03_Probability/14. Two Flips 2-pT0FXiH_5nI.it.vtt 213 BytesPart 02-Module 01-Lesson 03_Probability/08. Loaded Coin 1-sNvQeSikRFY.hr.vtt 213 BytesPart 02-Module 01-Lesson 04_Conditional Probability/12. Medical Example 3-Rf6WfB_1EJQ.zh-CN.vtt 212 BytesPart 02-Module 01-Lesson 03_Probability/08. Loaded Coin 1-sNvQeSikRFY.it.vtt 212 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/22. Disease Test 3-a61GPGk-Qy4.pt-BR.vtt 212 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-goEMc0w58xM.ar.vtt 211 BytesPart 02-Module 01-Lesson 11_Robot Localization/25. Move 1000-x2o1g3J-1nw.ja.vtt 211 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-PE-k3PGXeLY.es-ES.vtt 211 BytesPart 02-Module 01-Lesson 03_Probability/15. Two Flips 3-uimwo-puQWY.it.vtt 210 BytesPart 02-Module 01-Lesson 03_Probability/15. Two Flips 3-uimwo-puQWY.en.vtt 210 BytesPart 02-Module 01-Lesson 03_Probability/08. Loaded Coin 1-sNvQeSikRFY.es-ES.vtt 210 BytesPart 02-Module 01-Lesson 03_Probability/16. Two Flips 4-rRPwknIDuI0.pt-BR.vtt 209 BytesPart 02-Module 01-Lesson 11_Robot Localization/25. Move 1000-x2o1g3J-1nw.pt-PT.vtt 209 BytesPart 02-Module 01-Lesson 11_Robot Localization/12. Sum of Probabilities-6c0XvswnGm0.ja.vtt 208 BytesPart 02-Module 01-Lesson 11_Robot Localization/05. Uniform Probability Quiz-IZC33Tmy8Lo.ru.vtt 207 BytesPart 02-Module 01-Lesson 03_Probability/14. Two Flips 2-pT0FXiH_5nI.ar.vtt 207 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/30. Robot Sensing 4-d_fbDqAGVdE.zh-CN.vtt 207 BytesPart 02-Module 01-Lesson 11_Robot Localization/25. Move 1000-x2o1g3J-1nw.pt.vtt 206 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-UERKMwmkAsM.th.vtt 205 BytesPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/09. Measurement and Motion 2-1X8Tu6TmKhY.en.vtt 204 BytesPart 02-Module 01-Lesson 03_Probability/14. Two Flips 2-pT0FXiH_5nI.hr.vtt 204 BytesPart 02-Module 01-Lesson 04_Conditional Probability/14. Medical Example 5-fqt7NIvMB0s.th.vtt 204 BytesPart 02-Module 01-Lesson 11_Robot Localization/25. Move 1000-x2o1g3J-1nw.en.vtt 203 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/30. Robot Sensing 4-d_fbDqAGVdE.pt-BR.vtt 202 BytesPart 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-WgX17_mmc1c.bn.vtt 201 BytesPart 02-Module 01-Lesson 03_Probability/08. Loaded Coin 1-sNvQeSikRFY.ja.vtt 201 BytesPart 02-Module 01-Lesson 03_Probability/08. Loaded Coin 1-sNvQeSikRFY.pt-BR.vtt 201 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/34. Robot Sensing 8-hyAQ28MYmc4.ja.vtt 200 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/12. Normalizing 3-V96RcbbVP7Q.ja.vtt 199 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/12. Normalizing 3-V96RcbbVP7Q.zh-CN.vtt 198 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/30. Robot Sensing 4-d_fbDqAGVdE.ja.vtt 198 BytesPart 02-Module 01-Lesson 03_Probability/14. Two Flips 2-pT0FXiH_5nI.en.vtt 198 BytesPart 02-Module 01-Lesson 03_Probability/15. Two Flips 3-uimwo-puQWY.hr.vtt 197 BytesPart 02-Module 01-Lesson 03_Probability/07. Fair Coin-fSKL742j-zk.zh-CN.vtt 197 BytesPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/09. Measurement and Motion 2-1X8Tu6TmKhY.zh-CN.vtt 196 BytesPart 02-Module 01-Lesson 03_Probability/14. Two Flips 2-pT0FXiH_5nI.zh-CN.vtt 196 BytesPart 02-Module 01-Lesson 03_Probability/14. Two Flips 2-pT0FXiH_5nI.ja.vtt 194 BytesPart 02-Module 01-Lesson 03_Probability/15. Two Flips 3-uimwo-puQWY.ja.vtt 194 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-PE-k3PGXeLY.it.vtt 193 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-PE-k3PGXeLY.en.vtt 193 BytesPart 02-Module 01-Lesson 03_Probability/08. Loaded Coin 1-sNvQeSikRFY.zh-CN.vtt 192 BytesPart 02-Module 01-Lesson 03_Probability/07. Fair Coin-fSKL742j-zk.es-ES.vtt 192 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-PE-k3PGXeLY.zh-CN.vtt 192 BytesPart 02-Module 01-Lesson 04_Conditional Probability/15. Medical Example 6-iyE5h48qPFQ.ar.vtt 191 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/16. Cancer Probabilities-7ZLe_JP5wRY.ar.vtt 190 BytesPart 02-Module 01-Lesson 03_Probability/07. Fair Coin-fSKL742j-zk.en.vtt 190 BytesPart 02-Module 01-Lesson 08_Probability Distributions/14. Range Probability 2-GMC_T-hbTlc.es-ES.vtt 189 BytesPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/09. Measurement and Motion 2-1X8Tu6TmKhY.ja.vtt 187 BytesPart 02-Module 01-Lesson 04_Conditional Probability/16. Medical Example 7-cw_zgQbAWNU.ja.vtt 187 BytesPart 02-Module 01-Lesson 03_Probability/14. Two Flips 2-pT0FXiH_5nI.pt-BR.vtt 186 BytesPart 02-Module 01-Lesson 08_Probability Distributions/14. Range Probability 2-GMC_T-hbTlc.en.vtt 186 BytesPart 02-Module 01-Lesson 03_Probability/09. Loaded Coin 2-Y7tnbth-gag.es-ES.vtt 185 BytesPart 02-Module 01-Lesson 03_Probability/09. Loaded Coin 2-Y7tnbth-gag.pt-BR.vtt 184 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/21. Disease Test 2-GsneDVJB75E.ja.vtt 184 BytesPart 02-Module 01-Lesson 04_Conditional Probability/16. Medical Example 7-cw_zgQbAWNU.pt-BR.vtt 183 BytesPart 03-Module 01-Lesson 02_Introduction to Kalman Filters/17. Gaussian Motion-xNPEjY4dsds.ja.vtt 181 BytesPart 02-Module 01-Lesson 03_Probability/09. Loaded Coin 2-Y7tnbth-gag.en.vtt 180 BytesPart 02-Module 01-Lesson 11_Robot Localization/06. Uniform Distribution-_sAkAALHyEg.es-ES.vtt 180 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/21. Disease Test 2-GsneDVJB75E.th.vtt 178 BytesPart 02-Module 01-Lesson 03_Probability/07. Fair Coin-fSKL742j-zk.it.vtt 178 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-clFL503NPyY.th.vtt 177 BytesPart 02-Module 01-Lesson 03_Probability/15. Two Flips 3-uimwo-puQWY.zh-CN.vtt 177 BytesPart 02-Module 01-Lesson 11_Robot Localization/06. Uniform Distribution-_sAkAALHyEg.es.vtt 177 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/13. Total Probability-_hXCgF-aMB0.ar.vtt 176 BytesPart 02-Module 01-Lesson 11_Robot Localization/06. Uniform Distribution-_sAkAALHyEg.zh-CN.vtt 176 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/32. Robot Sensing 6-Se-ddM2Wdac.ja.vtt 176 BytesPart 02-Module 01-Lesson 11_Robot Localization/25. Move 1000-x2o1g3J-1nw.zh-CN.vtt 175 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/32. Robot Sensing 6-Se-ddM2Wdac.ar.vtt 175 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-PE-k3PGXeLY.pt-PT.vtt 175 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-goEMc0w58xM.ja.vtt 175 BytesPart 02-Module 01-Lesson 11_Robot Localization/06. Uniform Distribution-_sAkAALHyEg.it.vtt 175 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/16. Cancer Probabilities-7ZLe_JP5wRY.it.vtt 174 BytesPart 02-Module 01-Lesson 04_Conditional Probability/16. Medical Example 7-cw_zgQbAWNU.es-ES.vtt 174 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-goEMc0w58xM.es-ES.vtt 174 BytesPart 02-Module 01-Lesson 03_Probability/07. Fair Coin-fSKL742j-zk.pt-BR.vtt 173 BytesPart 02-Module 01-Lesson 11_Robot Localization/05. Uniform Probability Quiz-IZC33Tmy8Lo.pt-PT.vtt 173 BytesPart 02-Module 01-Lesson 11_Robot Localization/05. Uniform Probability Quiz-IZC33Tmy8Lo.es-ES.vtt 172 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-PE-k3PGXeLY.pt.vtt 172 BytesPart 02-Module 01-Lesson 03_Probability/09. Loaded Coin 2-Y7tnbth-gag.it.vtt 171 BytesPart 02-Module 01-Lesson 04_Conditional Probability/16. Medical Example 7-cw_zgQbAWNU.it.vtt 171 BytesPart 02-Module 01-Lesson 11_Robot Localization/06. Uniform Distribution-_sAkAALHyEg.en.vtt 170 BytesPart 02-Module 01-Lesson 11_Robot Localization/06. Uniform Distribution-_sAkAALHyEg.pt-PT.vtt 170 BytesPart 02-Module 01-Lesson 11_Robot Localization/05. Uniform Probability Quiz-IZC33Tmy8Lo.pt.vtt 170 BytesPart 02-Module 01-Lesson 04_Conditional Probability/15. Medical Example 6-iyE5h48qPFQ.en.vtt 169 BytesPart 02-Module 01-Lesson 11_Robot Localization/05. Uniform Probability Quiz-IZC33Tmy8Lo.es.vtt 169 BytesPart 02-Module 01-Lesson 11_Robot Localization/06. Uniform Distribution-_sAkAALHyEg.ja.vtt 169 BytesPart 02-Module 01-Lesson 04_Conditional Probability/14. Medical Example 5-fqt7NIvMB0s.pt-BR.vtt 169 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-goEMc0w58xM.pt-BR.vtt 169 BytesPart 02-Module 01-Lesson 11_Robot Localization/06. Uniform Distribution-_sAkAALHyEg.pt.vtt 167 BytesPart 02-Module 01-Lesson 04_Conditional Probability/16. Medical Example 7-cw_zgQbAWNU.en.vtt 167 BytesPart 02-Module 01-Lesson 04_Conditional Probability/15. Medical Example 6-iyE5h48qPFQ.es-ES.vtt 166 BytesPart 02-Module 01-Lesson 08_Probability Distributions/14. Range Probability 2-GMC_T-hbTlc.zh-CN.vtt 166 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/16. Cancer Probabilities-7ZLe_JP5wRY.es-ES.vtt 165 BytesPart 02-Module 01-Lesson 04_Conditional Probability/10. Medical Example 1-E1ph6NP3_v4.th.vtt 164 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/13. Total Probability-_hXCgF-aMB0.pt-BR.vtt 164 BytesPart 02-Module 01-Lesson 04_Conditional Probability/15. Medical Example 6-iyE5h48qPFQ.it.vtt 164 BytesPart 02-Module 01-Lesson 11_Robot Localization/30. Formal Definition of Probability 1-OQ2JS2wQzrs.pt-PT.vtt 164 BytesPart 02-Module 01-Lesson 03_Probability/09. Loaded Coin 2-Y7tnbth-gag.zh-CN.vtt 164 BytesPart 02-Module 01-Lesson 04_Conditional Probability/15. Medical Example 6-iyE5h48qPFQ.pt-BR.vtt 164 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-W5i-gRAvZxs.ar.vtt 163 BytesPart 02-Module 01-Lesson 04_Conditional Probability/15. Medical Example 6-iyE5h48qPFQ.zh-CN.vtt 163 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-W5i-gRAvZxs.pt-BR.vtt 162 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-UERKMwmkAsM.ar.vtt 161 BytesPart 02-Module 01-Lesson 11_Robot Localization/30. Formal Definition of Probability 1-OQ2JS2wQzrs.pt.vtt 161 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/24. Disease Test 5-4qW7a5E74No.th.vtt 160 BytesPart 02-Module 01-Lesson 03_Probability/09. Loaded Coin 2-Y7tnbth-gag.ja.vtt 159 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/21. Disease Test 2-GsneDVJB75E.ar.vtt 158 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/16. Cancer Probabilities-7ZLe_JP5wRY.zh-CN.vtt 158 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-goEMc0w58xM.zh-CN.vtt 158 BytesPart 02-Module 01-Lesson 03_Probability/09. Loaded Coin 2-Y7tnbth-gag.hr.vtt 157 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/32. Robot Sensing 6-Se-ddM2Wdac.pt-BR.vtt 157 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/32. Robot Sensing 6-Se-ddM2Wdac.es-ES.vtt 157 BytesPart 02-Module 01-Lesson 03_Probability/07. Fair Coin-fSKL742j-zk.hr.vtt 155 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-goEMc0w58xM.en.vtt 155 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/21. Disease Test 2-GsneDVJB75E.es-ES.vtt 155 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/16. Cancer Probabilities-7ZLe_JP5wRY.ja.vtt 155 BytesPart 02-Module 01-Lesson 11_Robot Localization/30. Formal Definition of Probability 1-OQ2JS2wQzrs.it.vtt 153 BytesPart 02-Module 01-Lesson 04_Conditional Probability/14. Medical Example 5-fqt7NIvMB0s.ar.vtt 153 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-ztkKTrMZHXg.th.vtt 152 BytesPart 02-Module 01-Lesson 04_Conditional Probability/16. Medical Example 7-cw_zgQbAWNU.zh-CN.vtt 152 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/16. Cancer Probabilities-7ZLe_JP5wRY.en.vtt 152 BytesPart 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-WgX17_mmc1c.ru.vtt 150 BytesPart 02-Module 01-Lesson 11_Robot Localization/05. Uniform Probability Quiz-IZC33Tmy8Lo.en.vtt 150 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/21. Disease Test 2-GsneDVJB75E.zh-CN.vtt 149 BytesPart 02-Module 01-Lesson 03_Probability/07. Fair Coin-fSKL742j-zk.ja.vtt 149 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/32. Robot Sensing 6-Se-ddM2Wdac.zh-CN.vtt 149 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/21. Disease Test 2-GsneDVJB75E.pt-BR.vtt 149 BytesPart 02-Module 01-Lesson 11_Robot Localization/30. Formal Definition of Probability 1-OQ2JS2wQzrs.es-ES.vtt 147 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/32. Robot Sensing 6-Se-ddM2Wdac.en.vtt 147 BytesPart 02-Module 01-Lesson 04_Conditional Probability/10. Medical Example 1-E1ph6NP3_v4.pt-BR.vtt 146 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-G9yQ_URDrDQ.ar.vtt 144 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/13. Total Probability-_hXCgF-aMB0.es-ES.vtt 143 BytesPart 02-Module 01-Lesson 11_Robot Localization/30. Formal Definition of Probability 1-OQ2JS2wQzrs.en.vtt 142 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/13. Total Probability-_hXCgF-aMB0.ja.vtt 142 BytesPart 02-Module 01-Lesson 04_Conditional Probability/14. Medical Example 5-fqt7NIvMB0s.es-ES.vtt 142 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/21. Disease Test 2-GsneDVJB75E.en.vtt 142 BytesPart 02-Module 01-Lesson 08_Probability Distributions/14. Range Probability 2-GMC_T-hbTlc.ja.vtt 141 BytesPart 02-Module 01-Lesson 04_Conditional Probability/10. Medical Example 1-E1ph6NP3_v4.ja.vtt 141 BytesPart 02-Module 01-Lesson 04_Conditional Probability/15. Medical Example 6-iyE5h48qPFQ.ja.vtt 141 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/13. Total Probability-_hXCgF-aMB0.en.vtt 140 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-W5i-gRAvZxs.es-ES.vtt 140 BytesPart 02-Module 01-Lesson 04_Conditional Probability/10. Medical Example 1-E1ph6NP3_v4.it.vtt 138 BytesPart 02-Module 01-Lesson 04_Conditional Probability/14. Medical Example 5-fqt7NIvMB0s.ja.vtt 138 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-G9yQ_URDrDQ.es-ES.vtt 138 BytesPart 02-Module 01-Lesson 11_Robot Localization/05. Uniform Probability Quiz-IZC33Tmy8Lo.it.vtt 138 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/31. Robot Sensing 5-tIrqdYTT_9Q.th.vtt 137 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-W5i-gRAvZxs.en.vtt 136 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/12. Normalizing 3-etrUbOAoh1U.th.vtt 135 BytesPart 02-Module 01-Lesson 11_Robot Localization/30. Formal Definition of Probability 1-OQ2JS2wQzrs.ja.vtt 135 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-W5i-gRAvZxs.ja.vtt 134 BytesPart 02-Module 01-Lesson 11_Robot Localization/05. Uniform Probability Quiz-IZC33Tmy8Lo.ja.vtt 133 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-G9yQ_URDrDQ.ja.vtt 132 BytesPart 02-Module 01-Lesson 04_Conditional Probability/10. Medical Example 1-E1ph6NP3_v4.ar.vtt 132 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/22. Disease Test 3-PfEYA6z-19w.th.vtt 130 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/13. Total Probability-_hXCgF-aMB0.it.vtt 129 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-UERKMwmkAsM.es-ES.vtt 129 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-G9yQ_URDrDQ.en.vtt 129 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-G9yQ_URDrDQ.zh-CN.vtt 129 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/22. Disease Test 3-PfEYA6z-19w.ar.vtt 129 BytesPart 02-Module 01-Lesson 04_Conditional Probability/14. Medical Example 5-fqt7NIvMB0s.en.vtt 128 BytesPart 02-Module 01-Lesson 11_Robot Localization/05. Uniform Probability Quiz-IZC33Tmy8Lo.zh-CN.vtt 128 BytesPart 02-Module 01-Lesson 04_Conditional Probability/14. Medical Example 5-fqt7NIvMB0s.it.vtt 127 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/13. Total Probability-_hXCgF-aMB0.zh-CN.vtt 127 BytesPart 02-Module 01-Lesson 08_Probability Distributions/14. Range Probability 2-xFFxdNj6pTA.es-ES.vtt 126 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-UERKMwmkAsM.ja.vtt 126 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-clFL503NPyY.ar.vtt 126 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-G9yQ_URDrDQ.pt-BR.vtt 125 BytesPart 02-Module 01-Lesson 04_Conditional Probability/10. Medical Example 1-E1ph6NP3_v4.es-ES.vtt 125 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-UERKMwmkAsM.pt-BR.vtt 123 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/31. Robot Sensing 5-tIrqdYTT_9Q.ja.vtt 123 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/18. Normalizer-W5i-gRAvZxs.zh-CN.vtt 123 BytesPart 02-Module 01-Lesson 04_Conditional Probability/14. Medical Example 5-fqt7NIvMB0s.zh-CN.vtt 123 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/24. Disease Test 5-4qW7a5E74No.ja.vtt 123 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/22. Disease Test 3-PfEYA6z-19w.ja.vtt 122 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/24. Disease Test 5-4qW7a5E74No.ar.vtt 122 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/24. Disease Test 5-4qW7a5E74No.pt-BR.vtt 122 BytesPart 02-Module 01-Lesson 08_Probability Distributions/14. Range Probability 2-xFFxdNj6pTA.zh-CN.vtt 121 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-UERKMwmkAsM.en.vtt 120 BytesPart 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-WgX17_mmc1c.es-ES.vtt 120 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/24. Disease Test 5-4qW7a5E74No.es-ES.vtt 120 BytesPart 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-WgX17_mmc1c.ja.vtt 119 BytesPart 02-Module 01-Lesson 04_Conditional Probability/10. Medical Example 1-E1ph6NP3_v4.en.vtt 119 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-clFL503NPyY.es-ES.vtt 118 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/31. Robot Sensing 5-tIrqdYTT_9Q.ar.vtt 118 BytesPart 02-Module 01-Lesson 04_Conditional Probability/10. Medical Example 1-E1ph6NP3_v4.zh-CN.vtt 118 BytesPart 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-WgX17_mmc1c.es.vtt 117 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-UERKMwmkAsM.zh-CN.vtt 116 BytesPart 02-Module 01-Lesson 08_Probability Distributions/14. Range Probability 2-xFFxdNj6pTA.en.vtt 116 BytesPart 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-WgX17_mmc1c.zh-CN.vtt 115 BytesPart 02-Module 01-Lesson 08_Probability Distributions/14. Range Probability 2-xFFxdNj6pTA.ja.vtt 115 BytesPart 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-WgX17_mmc1c.en.vtt 113 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/22. Disease Test 3-PfEYA6z-19w.zh-CN.vtt 113 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-clFL503NPyY.ja.vtt 113 BytesPart 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-WgX17_mmc1c.it.vtt 111 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/24. Disease Test 5-4qW7a5E74No.zh-CN.vtt 111 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/12. Normalizing 3-etrUbOAoh1U.ar.vtt 110 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/31. Robot Sensing 5-tIrqdYTT_9Q.zh-CN.vtt 110 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-ztkKTrMZHXg.ja.vtt 110 BytesPart 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-WgX17_mmc1c.pt-PT.vtt 110 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/24. Disease Test 5-4qW7a5E74No.en.vtt 110 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/11. Normalizing 2--pOzdj6pnbA.es-ES.vtt 109 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/12. Normalizing 3-etrUbOAoh1U.es-ES.vtt 109 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-clFL503NPyY.en.vtt 109 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-clFL503NPyY.zh-CN.vtt 108 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/33. Robot Sensing 7-clFL503NPyY.pt-BR.vtt 108 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/31. Robot Sensing 5-tIrqdYTT_9Q.es-ES.vtt 108 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/12. Normalizing 3-etrUbOAoh1U.pt-BR.vtt 108 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/11. Normalizing 2--pOzdj6pnbA.th.vtt 108 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/22. Disease Test 3-PfEYA6z-19w.es-ES.vtt 107 BytesPart 02-Module 01-Lesson 11_Robot Localization/09. Compute Sum-WgX17_mmc1c.pt.vtt 107 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/31. Robot Sensing 5-tIrqdYTT_9Q.pt-BR.vtt 106 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-uw51WQDqXAI.es-ES.vtt 105 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/22. Disease Test 3-PfEYA6z-19w.en.vtt 104 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/12. Normalizing 3-etrUbOAoh1U.en.vtt 103 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-uw51WQDqXAI.ja.vtt 102 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-ztkKTrMZHXg.es-ES.vtt 101 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/22. Disease Test 3-PfEYA6z-19w.pt-BR.vtt 99 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-ztkKTrMZHXg.zh-CN.vtt 98 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-uw51WQDqXAI.pt-PT.vtt 98 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/31. Robot Sensing 5-tIrqdYTT_9Q.en.vtt 97 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-uw51WQDqXAI.en.vtt 96 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/12. Normalizing 3-etrUbOAoh1U.it.vtt 96 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-ztkKTrMZHXg.ar.vtt 96 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-uw51WQDqXAI.pt.vtt 95 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/11. Normalizing 2--pOzdj6pnbA.ar.vtt 95 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-ztkKTrMZHXg.en.vtt 95 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/12. Normalizing 3-etrUbOAoh1U.ja.vtt 94 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/23. Disease Test 4-ztkKTrMZHXg.pt-BR.vtt 94 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-uw51WQDqXAI.it.vtt 93 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/11. Normalizing 2--pOzdj6pnbA.pt-BR.vtt 92 BytesPart 02-Module 01-Lesson 11_Robot Localization/31. Formal Definition of Probability 2-uw51WQDqXAI.zh-CN.vtt 91 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/11. Normalizing 2--pOzdj6pnbA.ja.vtt 91 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/12. Normalizing 3-etrUbOAoh1U.zh-CN.vtt 90 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/11. Normalizing 2--pOzdj6pnbA.it.vtt 90 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/11. Normalizing 2--pOzdj6pnbA.en.vtt 89 BytesPart 02-Module 01-Lesson 06_Bayes' Rule/11. Normalizing 2--pOzdj6pnbA.zh-CN.vtt 87 Bytes
20078 driving test highway code and driving theory 4.0 GB
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