Name UDACITY - Artificial Intelligence AI for Trading v1.0.0

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Size 5.86GB

UpdateDate 2024-11-24

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Files Part 06-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.tr.vtt | 81B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.zh-CN.vtt | 83B Part 06-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.hr.vtt | 83B Part 06-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.zh-CN.vtt | 84B Part 06-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.zh-CN.vtt | 84B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.hr.vtt | 85B Part 06-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.hr.vtt | 85B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.zh-Hans.vtt | 85B Part 06-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.en.vtt | 86B Part 06-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.hr.vtt | 86B Part 06-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.en.vtt | 86B Part 06-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.zh-CN.vtt | 87B Part 06-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.hr.vtt | 87B Part 06-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.it.vtt | 87B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.it.vtt | 88B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.ja.vtt | 88B Part 06-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.ja.vtt | 88B Part 06-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.en.vtt | 88B Part 06-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.pt-BR.vtt | 89B Part 06-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.en.vtt | 89B Part 06-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.ja.vtt | 89B Part 06-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.it.vtt | 89B Part 06-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.pt-BR.vtt | 89B Part 06-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.pt-PT.vtt | 89B Part 06-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.it.vtt | 89B Part 06-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.it.vtt | 89B Part 06-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.zh-CN.vtt | 90B Part 06-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.ar.vtt | 90B Part 06-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.en.vtt | 90B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.zh-CN.vtt | 90B Part 06-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.it.vtt | 90B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.en.vtt | 90B Part 06-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.ja.vtt | 91B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.pt-BR.vtt | 91B Part 06-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.pt-BR.vtt | 92B Part 06-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.ar.vtt | 92B Part 06-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.zh-CN.vtt | 94B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.it.vtt | 94B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.ja.vtt | 94B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.ar.vtt | 94B Part 06-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.pt-BR.vtt | 94B Part 06-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.en.vtt | 95B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.en.vtt | 95B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.hr.vtt | 95B Part 06-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.ar.vtt | 95B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.es-ES.vtt | 95B Part 06-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.es-ES.vtt | 95B Part 06-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.ar.vtt | 96B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.it.vtt | 96B Part 06-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.ja.vtt | 97B Part 06-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.en.vtt | 97B Part 06-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.ar.vtt | 98B Part 06-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.zh-Hans.vtt | 98B Part 06-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.zh-CN.vtt | 98B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.pt-BR.vtt | 99B Part 06-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.pt-BR.vtt | 99B Part 06-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.ar.vtt | 99B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.zh-CN.vtt | 99B Part 06-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.pt-BR.vtt | 100B Part 06-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.ja.vtt | 100B Part 06-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.es-ES.vtt | 101B Part 06-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.pt-BR.vtt | 101B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.zh-Hans.vtt | 101B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.en.vtt | 103B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.es-ES.vtt | 104B Part 06-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.en.vtt | 104B Part 06-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.pt-BR.vtt | 106B Part 06-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.es-ES.vtt | 107B Part 06-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.th.vtt | 108B Part 06-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.zh-CN.vtt | 108B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.ar.vtt | 108B Part 06-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.es-ES.vtt | 108B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.pt-BR.vtt | 108B Part 06-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.pt-BR.vtt | 108B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.es-ES.vtt | 109B Part 06-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.en.vtt | 109B Part 06-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.es-ES.vtt | 109B Part 06-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.ja.vtt | 110B Part 06-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.zh-CN.vtt | 110B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.ar.vtt | 110B Part 06-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.en.vtt | 110B Part 06-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.zh-CN.vtt | 111B Part 06-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.zh-CN.vtt | 113B Part 06-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.zh-CN.vtt | 113B Part 06-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.ja.vtt | 113B Part 06-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.zh-CN.vtt | 115B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.ja.vtt | 116B Part 06-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.zh-CN.vtt | 116B Part 06-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.zh-CN.vtt | 117B Part 06-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.zh-CN.vtt | 118B Part 06-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.ja.vtt | 118B Part 06-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.ar.vtt | 118B Part 06-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.es-ES.vtt | 118B Part 06-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.en.vtt | 118B Part 06-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.zh-Hans.vtt | 119B Part 06-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.en.vtt | 119B Part 06-Module 01-Lesson 07_Bayes Rule/18. 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Loaded Coin 2-Y7tnbth-gag.it.vtt | 171B Part 06-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.it.vtt | 173B Part 06-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.pt-BR.vtt | 173B Part 06-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.pt-BR.vtt | 173B Part 06-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.es-ES.vtt | 174B Part 06-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.it.vtt | 174B Part 06-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.es-ES.vtt | 174B Part 06-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.ja.vtt | 175B Part 06-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.ar.vtt | 175B Part 06-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.ar.vtt | 176B Part 06-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.ja.vtt | 176B Part 06-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.th.vtt | 177B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.zh-CN.vtt | 177B Part 06-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.th.vtt | 178B Part 06-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.it.vtt | 178B Part 06-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.en.vtt | 180B Part 06-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.ja.vtt | 180B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.zh-CN.vtt | 180B Part 06-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.zh-CN.vtt | 182B Part 06-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.pt-BR.vtt | 183B Part 06-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.ja.vtt | 184B Part 06-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.ar.vtt | 184B Part 06-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.pt-BR.vtt | 184B Part 06-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.es-ES.vtt | 185B Part 06-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.pt-BR.vtt | 186B Part 06-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.zh-CN.vtt | 186B Part 06-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.ja.vtt | 187B Part 06-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.it.vtt | 187B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.zh-Hans.vtt | 189B Part 06-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.en.vtt | 190B Part 06-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.ar.vtt | 190B Part 06-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.ja.vtt | 190B Part 06-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.ar.vtt | 191B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.zh-CN.vtt | 192B Part 06-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.es-ES.vtt | 192B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.ja.vtt | 194B Part 06-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.ja.vtt | 194B Part 06-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.zh-CN.vtt | 196B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.en.vtt | 196B Part 06-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.ja.vtt | 197B Part 06-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.zh-CN.vtt | 197B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.hr.vtt | 197B Part 06-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.ja.vtt | 198B Part 06-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.en.vtt | 198B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.zh-CN.vtt | 198B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.ja.vtt | 199B Part 06-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.ja.vtt | 200B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.ja.vtt | 201B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.pt-BR.vtt | 201B Part 06-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.ar.vtt | 202B Part 06-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.pt-BR.vtt | 202B Part 06-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.ja.vtt | 202B Part 06-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.hr.vtt | 204B Part 07-Module 01-Lesson 03_Clustering/09. Handoff to Katie-knrPsGtpyQY.pt-BR.vtt | 204B Part 06-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.th.vtt | 204B Part 06-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.ar.vtt | 204B Part 06-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.th.vtt | 205B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.it.vtt | 205B Part 07-Module 01-Lesson 03_Clustering/09. Handoff to Katie-knrPsGtpyQY.zh-CN.vtt | 206B Part 07-Module 01-Lesson 03_Clustering/09. Handoff to Katie-knrPsGtpyQY.en.vtt | 207B Part 06-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.zh-CN.vtt | 207B Part 06-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.ar.vtt | 207B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.ar.vtt | 208B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.hr.vtt | 209B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.pt-BR.vtt | 209B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.es-ES.vtt | 210B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.en.vtt | 210B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.it.vtt | 210B Part 06-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.zh-CN.vtt | 210B Part 06-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.ar.vtt | 211B Part 06-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.zh-CN.vtt | 212B Part 06-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.ja.vtt | 212B Part 06-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.zh-CN.vtt | 212B Part 06-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.pt-BR.vtt | 212B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.it.vtt | 212B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.hr.vtt | 213B Part 06-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.it.vtt | 213B Part 06-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.zh-CN.vtt | 214B Part 06-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.en.vtt | 214B Part 06-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.en.vtt | 214B Part 06-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.en.vtt | 214B Part 06-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.zh-CN.vtt | 215B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.pt-PT.vtt | 215B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.hr.vtt | 216B Part 06-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.en.vtt | 216B Part 06-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.zh-CN.vtt | 216B Part 06-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.pt-BR.vtt | 216B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.ja.vtt | 216B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.en.vtt | 217B Part 06-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.ja.vtt | 217B Part 06-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.es-ES.vtt | 217B Part 06-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.zh-CN.vtt | 218B Part 06-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.pt-BR.vtt | 218B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.en.vtt | 219B Part 06-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.es-ES.vtt | 219B Part 06-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.en.vtt | 219B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.pt-BR.vtt | 219B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.ja.vtt | 219B Part 06-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.es-ES.vtt | 221B Part 06-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.en.vtt | 222B Part 06-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.ar.vtt | 222B Part 06-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.ar.vtt | 222B Part 06-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.ar.vtt | 222B Part 06-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.pt-BR.vtt | 223B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.pt-BR.vtt | 223B Part 06-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.zh-CN.vtt | 225B Part 06-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.zh-CN.vtt | 226B Part 06-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.es-ES.vtt | 227B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.zh-CN.vtt | 228B Part 06-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.zh-CN.vtt | 228B Part 06-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.th.vtt | 228B Part 06-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.en.vtt | 231B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.it.vtt | 231B Part 06-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.es-ES.vtt | 231B Part 06-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.zh-CN.vtt | 232B Part 06-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.es-ES.vtt | 233B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.es-ES.vtt | 234B Part 06-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.es-ES.vtt | 234B Part 06-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.it.vtt | 234B Part 06-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.ja.vtt | 236B Part 06-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.es-ES.vtt | 236B Part 06-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.ja.vtt | 237B Part 06-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.en.vtt | 238B Part 06-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.es-ES.vtt | 238B Part 06-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.hr.vtt | 238B Part 06-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.ar.vtt | 238B Part 06-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.it.vtt | 239B Part 06-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.es-ES.vtt | 239B Part 06-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.en.vtt | 240B Part 06-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.pt-BR.vtt | 240B Part 06-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.it.vtt | 240B Part 06-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.th.vtt | 240B Part 06-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.th.vtt | 240B Part 06-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.en.vtt | 241B Part 06-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.zh-CN.vtt | 241B Part 06-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.ja.vtt | 241B Part 06-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.es-ES.vtt | 242B Part 06-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.es-ES.vtt | 243B Part 06-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.ja.vtt | 243B Part 06-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.th.vtt | 244B Part 06-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.zh-CN.vtt | 244B Part 06-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.en.vtt | 244B Part 06-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.en.vtt | 245B Part 06-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.en.vtt | 246B Part 06-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.pt-BR.vtt | 246B Part 06-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.ja.vtt | 247B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.en.vtt | 247B Part 06-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.ja.vtt | 247B Part 06-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.ja.vtt | 248B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.it.vtt | 248B Part 06-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.en.vtt | 248B Part 06-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.zh-CN.vtt | 248B Part 06-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.pt-BR.vtt | 249B Part 06-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.pt-BR.vtt | 249B Part 06-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.pt-BR.vtt | 249B Part 06-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.pt-BR.vtt | 249B Part 06-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.zh-CN.vtt | 250B Part 06-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.ar.vtt | 250B Part 06-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.es-ES.vtt | 251B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.es-ES.vtt | 252B Part 06-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.hr.vtt | 252B Part 06-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.ar.vtt | 252B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.th.vtt | 252B Part 06-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.pt-BR.vtt | 253B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.ar.vtt | 254B Part 06-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.ja.vtt | 254B Part 06-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.pt-BR.vtt | 254B Part 06-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.en.vtt | 256B Part 06-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.en.vtt | 256B Part 06-Module 01-Lesson 04_Probability/06. 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Medical Example 3-Rf6WfB_1EJQ.ja.vtt | 262B Part 06-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.ja.vtt | 264B Part 06-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.pt-BR.vtt | 265B Part 06-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.ar.vtt | 265B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.ar.vtt | 265B Part 06-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.th.vtt | 267B Part 06-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.zh-CN.vtt | 268B Part 06-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.en.vtt | 268B Part 06-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.pt-BR.vtt | 269B Part 06-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.es-ES.vtt | 272B Part 06-Module 01-Lesson 06_Conditional Probability/06. 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How Many Clusters-8Ygq5dRV0Kk.zh-CN.vtt | 385B Part 06-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.en.vtt | 387B Part 06-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.es-ES.vtt | 388B Part 06-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.ja.vtt | 389B Part 06-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.ja.vtt | 389B Part 06-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.es-ES.vtt | 389B Part 06-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.zh-CN.vtt | 389B Part 03-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.zh-CN.vtt | 389B Part 06-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.es-ES.vtt | 390B Part 08-Module 01-Lesson 01_Introduction to Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.zh-CN.vtt | 390B Part 06-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.ja.vtt | 390B Part 02-Module 02-Lesson 01_Introduction to Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.zh-CN.vtt | 390B Part 06-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.pt-BR.vtt | 391B Part 06-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.es-ES.vtt | 393B Part 06-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.th.vtt | 393B Part 06-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.pt-BR.vtt | 393B Part 06-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.ja.vtt | 395B Part 06-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.ar.vtt | 395B Part 06-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.pt-BR.vtt | 396B Part 06-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.ar.vtt | 396B Part 06-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.pt-BR.vtt | 397B Part 07-Module 01-Lesson 05_Introduction to Kalman Filters/09. Maximize Gaussian Solution - Artificial Intelligence for Robotics-2cD8T65E-jM.en.vtt | 397B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.ja.vtt | 397B Part 06-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.th.vtt | 398B Part 06-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.ar.vtt | 399B Part 06-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.en.vtt | 399B Part 06-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.ar.vtt | 399B Part 06-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.pt-BR.vtt | 401B Part 06-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.zh-CN.vtt | 403B Part 06-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.ja.vtt | 403B Part 06-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.zh-CN.vtt | 403B Part 06-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.ar.vtt | 404B Part 06-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.ar.vtt | 405B Part 06-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.es-ES.vtt | 406B Part 06-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.zh-CN.vtt | 408B Part 07-Module 01-Lesson 05_Introduction to Kalman Filters/09. Maximize Gaussian Solution - Artificial Intelligence for Robotics-2cD8T65E-jM.es-ES.vtt | 408B Part 06-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.zh-CN.vtt | 408B Part 06-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.it.vtt | 409B Part 03-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.zh-CN.vtt | 410B Part 06-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.pt-BR.vtt | 410B Part 06-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.pt-BR.vtt | 410B Part 03-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.pt-BR.vtt | 411B Part 06-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.zh-CN.vtt | 411B Part 06-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.ar.vtt | 411B Part 06-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.es-ES.vtt | 412B Part 06-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.en.vtt | 414B Part 06-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.it.vtt | 414B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.ja.vtt | 415B Part 06-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.th.vtt | 415B Part 06-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.en.vtt | 416B Part 06-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.ja.vtt | 417B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.es-ES.vtt | 417B Part 06-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.pt-BR.vtt | 418B Part 02-Module 02-Lesson 04_Training Neural Networks/10. Random Restart-idyBBCzXiqg.zh-CN.vtt | 419B Part 06-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.ja.vtt | 419B Part 02-Module 02-Lesson 01_Introduction to Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.en.vtt | 420B Part 06-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.zh-CN.vtt | 420B Part 06-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.ar.vtt | 420B Part 08-Module 01-Lesson 01_Introduction to Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.en.vtt | 420B Part 06-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.ja.vtt | 420B Part 06-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.pt-BR.vtt | 422B Part 06-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.zh-CN.vtt | 422B Part 06-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.it.vtt | 422B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.th.vtt | 423B Part 03-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.en.vtt | 423B Part 06-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.es-ES.vtt | 424B Part 06-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.en.vtt | 424B Part 07-Module 01-Lesson 03_Clustering/10. K-Means Cluster Visualization-ZMfwPUrOFsE.zh-CN.vtt | 424B Part 06-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.es-ES.vtt | 425B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.en.vtt | 425B Part 01-Module 02-Lesson 04_Time Series Modeling/09. M2L4 11 Outro V1-6sheR92KUU8.en.vtt | 425B Part 06-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.hr.vtt | 425B Part 06-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.es-ES.vtt | 426B Part 06-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.pt-BR.vtt | 427B Part 06-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.en.vtt | 427B Part 06-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.en.vtt | 428B Part 06-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.ja.vtt | 428B Part 06-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.zh-CN.vtt | 431B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.en.vtt | 432B Part 06-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.pt-BR.vtt | 433B Part 06-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.en.vtt | 433B Part 06-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.it.vtt | 433B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.it.vtt | 435B Part 06-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.ar.vtt | 436B Part 06-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.ar.vtt | 437B Part 07-Module 01-Lesson 03_Clustering/04. How Many Clusters-8Ygq5dRV0Kk.pt-BR.vtt | 439B Part 06-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.pt-BR.vtt | 440B Part 06-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.th.vtt | 441B Part 06-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.zh-CN.vtt | 441B Part 06-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.zh-CN.vtt | 442B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.pt-BR.vtt | 442B Part 06-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.ja.vtt | 444B Part 06-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.it.vtt | 444B Part 07-Module 01-Lesson 03_Clustering/07. Moving Centers 2-uC1Xwc7warg.ar.vtt | 444B Part 06-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.pt-BR.vtt | 444B Part 06-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.ar.vtt | 445B Part 06-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.pt-BR.vtt | 447B Part 06-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.th.vtt | 447B Part 06-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.ja.vtt | 449B Part 06-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.es-ES.vtt | 451B Part 07-Module 01-Lesson 03_Clustering/10. K-Means Cluster Visualization-ZMfwPUrOFsE.en.vtt | 451B Part 06-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.it.vtt | 452B Part 06-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.en.vtt | 453B Part 06-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.hr.vtt | 453B Part 07-Module 01-Lesson 03_Clustering/10. K-Means Cluster Visualization-ZMfwPUrOFsE.pt-BR.vtt | 454B Part 06-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.es-ES.vtt | 455B Part 06-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.en.vtt | 455B Part 06-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.zh-CN.vtt | 456B Part 03-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.zh-CN.vtt | 456B Part 06-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.ar.vtt | 456B Part 06-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.it.vtt | 456B Part 07-Module 01-Lesson 03_Clustering/04. How Many Clusters-8Ygq5dRV0Kk.en.vtt | 458B Part 06-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.ja.vtt | 458B Part 06-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.zh-CN.vtt | 458B Part 06-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.es-ES.vtt | 459B Part 06-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.ar.vtt | 459B Part 06-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.zh-CN.vtt | 460B Part 06-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.zh-CN.vtt | 460B Part 06-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.en.vtt | 461B Part 06-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.ar.vtt | 463B Part 06-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.pt-BR.vtt | 465B Part 06-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.es-ES.vtt | 466B Part 02-Module 02-Lesson 04_Training Neural Networks/10. Random Restart-idyBBCzXiqg.en.vtt | 466B Part 03-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.en.vtt | 467B Part 06-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.en.vtt | 468B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.hr.vtt | 469B Part 06-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.en.vtt | 470B Part 06-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.es-ES.vtt | 471B Part 06-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.es-ES.vtt | 471B Part 06-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.ar.vtt | 472B Part 06-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.ja.vtt | 473B Part 03-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.en.vtt | 473B Part 06-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.pt-BR.vtt | 473B Part 06-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.ar.vtt | 473B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.es-ES.vtt | 473B Part 06-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.pt-BR.vtt | 473B Part 06-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.ar.vtt | 473B Part 06-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.it.vtt | 476B Part 02-Module 02-Lesson 04_Training Neural Networks/10. Random Restart-idyBBCzXiqg.pt-BR.vtt | 478B Part 06-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.es-ES.vtt | 478B Part 06-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.en.vtt | 479B Part 07-Module 01-Lesson 03_Clustering/07. Moving Centers 2-FY0DXe0lfrI.ar.vtt | 479B Part 06-Module 01-Lesson 04_Probability/14. 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Optimizing Centers (Rubber Bands)-TN1rQMrx65c.zh-CN.vtt | 488B Part 06-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.ja.vtt | 491B Part 06-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.ar.vtt | 491B Part 06-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.ja.vtt | 492B Part 06-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.zh-CN.vtt | 492B Part 06-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.es-ES.vtt | 493B Part 06-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.ar.vtt | 493B Part 06-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.pt-BR.vtt | 495B Part 06-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.zh-CN.vtt | 495B Part 02-Module 02-Lesson 01_Introduction to Neural Networks/16. Quiz - Softmax-NNoezNnAMTY.en.vtt | 495B Part 06-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.en.vtt | 495B Part 08-Module 01-Lesson 01_Introduction to Neural Networks/16. Quiz - Softmax-NNoezNnAMTY.en.vtt | 495B Part 06-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.pt-BR.vtt | 496B Part 06-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.en.vtt | 496B Part 06-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.pt-BR.vtt | 497B Part 06-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.ar.vtt | 497B Part 06-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.pt-BR.vtt | 498B Part 06-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.zh-CN.vtt | 499B Part 06-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.pt-BR.vtt | 500B Part 02-Module 02-Lesson 01_Introduction to Neural Networks/16. Quiz - Softmax-NNoezNnAMTY.pt-BR.vtt | 501B Part 06-Module 01-Lesson 07_Bayes Rule/11. 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Quadratics 3-YSMWpFM92S0.zh-CN.vtt | 638B Part 06-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.hr.vtt | 640B Part 06-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.ar.vtt | 640B Part 06-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.pt-BR.vtt | 642B Part 06-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.zh-CN.vtt | 644B Part 03-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.en.vtt | 645B Part 06-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.en.vtt | 646B Part 06-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.ar.vtt | 650B Part 06-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.zh-CN.vtt | 650B Part 06-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.ar.vtt | 650B Part 03-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.ar.vtt | 652B Part 06-Module 01-Lesson 01_Descriptive Statistics - Part I/17. 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Robot Sensing 3-m1LSU9SPZ2k.ja.vtt | 657B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.zh-CN.vtt | 658B Part 06-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.ja.vtt | 661B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.hr.vtt | 662B Part 01-Module 03-Lesson 04_Portfolio Optimization/01. L4 01 Intro V1-CtIcmmR0YTs.en.vtt | 662B Part 06-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.ar.vtt | 663B Part 06-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.en.vtt | 663B Part 06-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.es-ES.vtt | 665B Part 07-Module 01-Lesson 03_Clustering/17. Counterintuitive Clusters 2-xSQTzAeeoEc.en.vtt | 665B Part 06-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.th.vtt | 667B Part 06-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.ja.vtt | 669B Part 06-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.ar.vtt | 670B Part 06-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.zh-CN.vtt | 670B Part 07-Module 01-Lesson 03_Clustering/05. Match Points with Clusters-wJV1cRjmIYY.pt-BR.vtt | 671B Part 06-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.es-ES.vtt | 671B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.es-ES.vtt | 671B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.it.vtt | 671B Part 07-Module 01-Lesson 03_Clustering/17. Counterintuitive Clusters 2-xSQTzAeeoEc.pt-BR.vtt | 672B Part 06-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.zh-CN.vtt | 673B Part 06-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.pt-BR.vtt | 673B Part 03-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.ar.vtt | 673B Part 06-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.zh-CN.vtt | 675B Part 06-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.en.vtt | 675B Part 06-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.zh-CN.vtt | 676B Part 06-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.th.vtt | 677B Part 06-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.es-ES.vtt | 679B Part 06-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.es-ES.vtt | 679B Part 06-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.ar.vtt | 679B Part 07-Module 01-Lesson 05_Introduction to Kalman Filters/15. KALMAN QUIZ Parameter Update 02 RENDER V2-vl6GkkEgY4M.en.vtt | 680B Part 07-Module 01-Lesson 03_Clustering/05. Match Points with Clusters-lS5DfbsWH34.zh-CN.vtt | 680B Part 06-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.pt-BR.vtt | 680B Part 06-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.es-ES.vtt | 681B Part 06-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.en.vtt | 682B Part 07-Module 01-Lesson 03_Clustering/05. Match Points with Clusters-wJV1cRjmIYY.ar.vtt | 682B Part 06-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.es-ES.vtt | 682B Part 06-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.en.vtt | 682B Part 06-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.ar.vtt | 684B Part 06-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.pt-BR.vtt | 684B Part 06-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.ar.vtt | 684B Part 06-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.ar.vtt | 684B Part 07-Module 01-Lesson 05_Introduction to Kalman Filters/13. KALMAN QUIZ Predicting The Peak 02 RENDER V1-mcwr6FcP2Vc.zh-CN.vtt | 686B Part 06-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.es-ES.vtt | 686B Part 06-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.pt-BR.vtt | 687B Part 06-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.pt-BR.vtt | 688B Part 02-Module 01-Lesson 04_Feature Extraction/10. NLP Summary-B9ul8fsQYOA.en.vtt | 688B Part 07-Module 01-Lesson 02_Naive Bayes/01. Naive Bayes Intro V2-vNOiQXghgRY.pt-BR.vtt | 690B Part 06-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.en.vtt | 690B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.hr.vtt | 690B Part 06-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.pt-BR.vtt | 691B Part 06-Module 01-Lesson 03_Admissions Case Study/04. 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Normalizing 1-9SbUxcyDTaQ.th.vtt | 700B Part 02-Module 02-Lesson 03_Recurrent Neural Networks/07. Remember Gate-0qlm86HaXuU.pt-BR.vtt | 700B Part 06-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.it.vtt | 702B Part 06-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.pt-BR.vtt | 702B Part 06-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.zh-CN.vtt | 704B Part 06-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.en.vtt | 704B Part 06-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.pt-BR.vtt | 705B Part 06-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.ar.vtt | 706B Part 06-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.zh-CN.vtt | 707B Part 06-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.zh-CN.vtt | 708B Part 06-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.ja.vtt | 708B Part 01-Module 02-Lesson 03_Regression/17. M2L3 15 Summary V1-n2VxcEcw0GY.en.vtt | 710B Part 06-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.ja.vtt | 710B Part 07-Module 01-Lesson 05_Introduction to Kalman Filters/20. Predict Function - Artificial Intelligence for Robotics-DV2cX9W0tT8.zh-CN.vtt | 711B Part 06-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.it.vtt | 712B Part 06-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.zh-CN.vtt | 713B Part 06-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.en.vtt | 714B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.en.vtt | 715B Part 06-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.en.vtt | 715B Part 06-Module 01-Lesson 09_Normal Distribution Theory/14. 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Conclusion-QRnLr7pwHyk.zh-CN.vtt | 724B Part 02-Module 01-Lesson 02_Intro to Natural Language Processing/03. Grammar-Jw3dA7xmoQ4.en.vtt | 727B Part 07-Module 01-Lesson 04_Decision Trees/12. MLND SL DT 10 Q Information Gain MAIN V1-tVLOLPEtLFw.zh-CN.vtt | 727B Part 10-Module 01-Lesson 01_Intro to NLP/04. Grammar-Jw3dA7xmoQ4.en.vtt | 727B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.pt-BR.vtt | 728B Part 06-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.es-ES.vtt | 728B Part 06-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.th.vtt | 729B Part 06-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.es-ES.vtt | 729B Part 06-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.ja.vtt | 730B Part 06-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.ar.vtt | 731B Part 06-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.en.vtt | 734B Part 02-Module 02-Lesson 03_Recurrent Neural Networks/07. Remember Gate-0qlm86HaXuU.en.vtt | 734B Part 06-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.pt-BR.vtt | 735B Part 06-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.pt-BR.vtt | 735B Part 06-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.pt-BR.vtt | 736B Part 06-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.ar.vtt | 738B Part 06-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.en.vtt | 738B Part 02-Module 02-Lesson 01_Introduction to Neural Networks/13. Error Functions-YfUUunxWIJw.zh-CN.vtt | 739B Part 08-Module 01-Lesson 01_Introduction to Neural Networks/13. Error Functions-YfUUunxWIJw.zh-CN.vtt | 739B Part 06-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.es-ES.vtt | 741B Part 06-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.pt-BR.vtt | 741B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.it.vtt | 742B Part 06-Module 01-Lesson 11_Confidence Intervals/16. Confidence Intervals And Hypothesis Tests-T2d9AUnWl-I.zh-CN.vtt | 742B Part 07-Module 01-Lesson 03_Clustering/04. How Many Clusters-R6oIvdBtsZw.zh-CN.vtt | 744B Part 06-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.pt-BR.vtt | 745B Part 03-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.zh-CN.vtt | 745B Part 06-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.zh-CN.vtt | 745B Part 06-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.es-ES.vtt | 746B Part 03-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.pt-BR.vtt | 746B Part 06-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.es-ES.vtt | 746B Part 06-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.hr.vtt | 748B Part 06-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.es-ES.vtt | 748B Part 06-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.ja.vtt | 748B Part 06-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.zh-CN.vtt | 750B Part 06-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.zh-CN.vtt | 751B Part 06-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.en.vtt | 752B Part 06-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.ar.vtt | 752B Part 06-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.zh-CN.vtt | 752B Part 06-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.pt-BR.vtt | 753B Part 06-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.en.vtt | 754B Part 06-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.es-ES.vtt | 757B Part 06-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.zh-CN.vtt | 759B Part 01-Module 03-Lesson 03_Portfolio Risk and Return/16. L3 13 Summary V1-I7XKJf8t_0s.en.vtt | 760B Part 06-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.ja.vtt | 760B Part 06-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.pt-BR.vtt | 761B Part 07-Module 01-Lesson 05_Introduction to Kalman Filters/20. Predict Function - Artificial Intelligence for Robotics-DV2cX9W0tT8.en.vtt | 762B Part 06-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.ja.vtt | 762B Part 06-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.zh-CN.vtt | 763B Part 03-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.en.vtt | 763B Part 06-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.it.vtt | 764B Part 06-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.ar.vtt | 765B Part 06-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.pt-PT.vtt | 765B Part 07-Module 01-Lesson 05_Introduction to Kalman Filters/09. Maximize Gaussian - Artificial Intelligence for Robotics-fRYtUP0P4Lg.zh-CN.vtt | 767B Part 06-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.it.vtt | 767B Part 07-Module 01-Lesson 03_Clustering/04. How Many Clusters-R6oIvdBtsZw.en.vtt | 768B Part 06-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.th.vtt | 768B Part 06-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.pt-BR.vtt | 769B Part 06-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.pt-BR.vtt | 769B Part 07-Module 01-Lesson 04_Decision Trees/12. MLND SL DT 10 Q Information Gain MAIN V1-tVLOLPEtLFw.en.vtt | 771B Part 06-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.th.vtt | 772B Part 07-Module 01-Lesson 03_Clustering/05. 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DL 27 Multi-Class Cross Entropy 2 Fix-keDswcqkees.mp4 | 4.14MB Part 08-Module 01-Lesson 01_Introduction to Neural Networks/22. DL 27 Multi-Class Cross Entropy 2 Fix-keDswcqkees.mp4 | 4.14MB Part 01-Module 03-Lesson 01_Stocks, Indices, Funds/10. L1 11 Adding Or Removing From An Index V2-_bWIZWa20j8.mp4 | 4.15MB Part 01-Module 03-Lesson 01_Stocks, Indices, Funds/09. L1 10 Market Cap Weighting V2-7qVVA5yLFnY.mp4 | 4.15MB Part 07-Module 01-Lesson 05_Introduction to Kalman Filters/01. 矩阵介绍-Ugx3mldc0lE.mp4 | 4.15MB Part 01-Module 03-Lesson 02_ETFs/08. L2 10 Lower Operational Costs And Taxes V2-UlJusglK0h0.mp4 | 4.16MB Part 06-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.mp4 | 4.16MB Part 07-Module 01-Lesson 04_Decision Trees/05. MLND SL DT 04 Q Student Admissions V3 MAIN V1-MOa335cQGI4.mp4 | 4.16MB Part 01-Module 04-Lesson 05_Risk Factor Models with PCA/16. 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L1 31 Transaction Costs V2-JGYAv7tQpyY.mp4 | 5.79MB Part 02-Module 02-Lesson 03_Recurrent Neural Networks/18. 05 Batching Data V1-9Eg0wf3eW-k.mp4 | 5.82MB Part 01-Module 04-Lesson 07_Alpha Factor Research Methods/10. M4 L3b 08 Winners And Losers Approximating Curves With Polynomials V4-Nw6v2EeECt0.mp4 | 5.83MB Part 06-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.mp4 | 5.84MB Part 01-Module 02-Lesson 03_Regression/15. M2L3 14 Regression In Trading V2-bcOGRWxg7qQ.mp4 | 5.86MB Part 03-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.mp4 | 5.90MB Part 02-Module 02-Lesson 02_Deep Learning with PyTorch/07. PyTorch V2 Part 1 Solution 3 V1-iMIo9p5iSbE.mp4 | 5.90MB Part 03-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Part II-1GRv1S6K8gQ.mp4 | 5.92MB Part 03-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.mp4 | 5.92MB Part 01-Module 04-Lesson 01_Factors/05. 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SL NB 01 Guess The Person V1 V1-tAOAjI-7ins.mp4 | 8.49MB Part 05-Module 01-Lesson 02_NumPy/07. NumPy 3 V1-Rt4aydeo9F8.mp4 | 8.50MB Part 01-Module 02-Lesson 02_Outliers and Filtering/07. M2L2 06 Spotting Outliers In Signal Returns V4-BSLGZz0RzTg.mp4 | 8.50MB Part 01-Module 02-Lesson 07_Project 2 Breakout Strategy/04. MV 10 Transition From Project 02 Int V1-DYjOsL3VYfY.mp4 | 8.51MB Part 01-Module 04-Lesson 07_Alpha Factor Research Methods/16. M4 L3b 12 Skewness And Momentum Momentum Enhances Or Weakened By Skew V2-S73J_h8DHsE.mp4 | 8.57MB Part 06-Module 01-Lesson 12_Hypothesis Testing/23. Connecting Errors and P-Values-hFNjd5l9CLs.mp4 | 8.58MB Part 04-Module 01-Lesson 01_Introduction/03. Essence Of Linear Algebra Intro -EHcxDZpeGFg.mp4 | 8.60MB Part 02-Module 01-Lesson 05_Financial Statements/11. M5 SC 6 Metacharacters Part 1 V1-Jay3euM62NQ.mp4 | 8.61MB Part 01-Module 04-Lesson 05_Risk Factor Models with PCA/13. 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