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Part 18 (1:39:37) ============ Part 06-Module 01-Lesson 12_Hypothesis Testing 0:00:00 23. Connecting Errors and P-Values-hFNjd5l9CLs 0:01:22 24. Conclusions In Hypothesis Testing-I0Mo7hcxahY 0:02:38 27. What If Our Sample Is Large-WoTCeSTL1eM 0:04:38 28. Multiple Testing Corrections-DuMgeHrkIF0 0:06:03 29. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA 0:07:09 32. Hypothesis Testing Conclusion-nQFchD4XPPs Part 06-Module 01-Lesson 13_Case Study AB tests 0:07:51 01. Case Study Introduction-J5uvdPxHIfs 0:08:14 02. AB Testing-EcWvhbIjT9o 0:10:23 04. Business Example-Wzz7omSDfEk 0:11:39 05. Experiment I-JLKAdT2JESk 0:13:27 07. Metric - Click Through Rate-EpfoKAwV_Eg 0:15:43 09. Experiment II-fq4eO7CybA4 0:16:26 11. Metric - Average Reading Duration-w6Y9ZxHDEbw 0:18:13 14. Analyzing Multiple Metrics-DtZghKNa7Ak 0:18:37 16. Drawing Conclusions-s-4ghG9vrGQ 0:19:26 18. Conclusion-qmGjRpMVBz8 Part 07-Module 01-Lesson 01_Linear Regression 0:19:51 01. Welcome To Linear Regression-zxZkTkM34BY 0:20:33 02. DLND REG 01 Quiz Housing Prices V2-8CSBiVKu35Q 0:21:38 03. Solution Housing Prices-uhdTulw9-Nc 0:22:15 04. Fitting A Line-gkdoknEEcaI 0:23:07 05. Moving A Line-8EIHFyL2Log 0:23:50 06. Absolute Trick-DJWjBAqSkZw 0:28:03 07. Square Trick-AGZEq-yQgRM 0:30:35 08. Gradient Descent-4s4x9h6AN5Y 0:33:54 09. Mean Absolute Error-vLKiY0Ehors 0:35:57 10. Mean Squared Error-MRyxmZDngI4 0:37:20 11. Minimizing Error Functions-RbT2TXN_6tY 0:40:14 14. Absolute Vs Squared Error-csvdjaqt1GM 0:40:44 14. DLND REG 12 Absolute Vs Squared Error 2 V1 (1)-7El1OH17Oi4 0:41:14 14. DLND REG 13 Absolute Vs Squared Error 3 V1 (1)-bIVGf_dDkrY 0:41:51 16. Higher Dimensions--UvpQV1qmiE 0:43:44 18. Closed Form Solution-G3fRVgLa5gI 0:45:52 21. Polynomial Regression-DBhWG-PagEQ 0:46:37 22. Regularization-PyFNIcsNma0 0:52:51 23. Conclusion-pyeojf0NniQ Part 07-Module 01-Lesson 02_Naive Bayes 0:53:08 01. Naive Bayes Intro V2-vNOiQXghgRY 0:53:31 02. SL NB 01 Guess The Person V1 V1-tAOAjI-7ins 0:55:32 03. SL NB 02 Known And Inferred V1 V2-DrYfZXiDLQI 0:56:21 04. SL NB 03 Guess The Person Now V1 V2-pQgO1KF90yU 1:01:26 05. SL NB 04 Bayes Theorem V1 V2-nVbPJmf53AI 1:03:29 06. SL NB 05 Q False Positives V1 V2-ngA6v09eP08 1:04:46 07. SL NB 06 S False Positives V1 V3-Bg6_Tvcv81A 1:09:24 08. SL NB 07 Q Bayesian Learning 1 V1 V4-J4BmsKXPnkA 1:10:50 09. SL NB 08 S Bayesian Learning 2 V1 V6-3rIYZgCXVXY 1:11:54 10. SL NB 09 Bayesian Learning 3 V1 V4-u-Hj4RsJn1o 1:14:04 11. MLND SL NB Naive Bayes Algorithm-CQBMB9jwcp8 1:18:10 12. MLND SL NB Solution Naive Bayes Algorithm-QDj3xzjuYmo Part 07-Module 01-Lesson 03_Clustering 1:19:20 02. Unsupervised Learning-Mx9f99bRB3Q 1:21:06 03. Clustering Movies-g8PKffm8IRY 1:22:56 04. How Many Clusters-8Ygq5dRV0Kk 1:23:12 04. How Many Clusters-R6oIvdBtsZw 1:23:41 05. Match Points with Clusters-lS5DfbsWH34 1:24:11 05. Match Points with Clusters-wJV1cRjmIYY 1:24:35 06. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc 1:25:35 06. Optimizing Centers (Rubber Bands)-TN1rQMrx65c 1:25:58 07. Moving Centers 2-FY0DXe0lfrI 1:26:11 07. Moving Centers 2-uC1Xwc7warg 1:26:25 08. Match Points (again)-5j6VZr8sHo8 1:27:10 08. Match Points (again)-9J3IwQFXveI 1:27:23 09. Handoff to Katie-knrPsGtpyQY 1:27:31 10. K-Means Cluster Visualization-iCTPBcowJRY 1:28:21 10. K-Means Cluster Visualization-ZMfwPUrOFsE 1:28:34 11. K-Means Clustering Visualization 2-fQXXa-CAoS0 1:30:32 12. K-Means Clustering Visualization 3-WfwX3B4d8_I 1:32:00 13. Sklearn-3zHUAXcoZ7c 1:35:45 14. Some challenges of k-means-e2CdlG5P4WA 1:36:02 15. Limitations of K-Means-4Fkfu37el_k 1:36:34 15. Limitations of K-Means-nvLhUSSUhiY 1:36:44 16. Counterintuitive Clusters-aveIz1JYeAg 1:37:22 16. Counterintuitive Clusters-StmEUgT1XSY 1:38:40 17. Counterintuitive Clusters 2-HyjBus7S2gY
