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Title: PracticalMachineLearning/VideoLectures at master · GooseCoder/PracticalMachineLearning · GitHub

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Description: Coursera course: Practical Machine Learning. Contribute to GooseCoder/PracticalMachineLearning development by creating an account on GitHub.

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1 - 1 - Prediction motivation (8-26).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%201%20-%20Prediction%20motivation%20(8-26).mp4
1 - 1 - Prediction motivation (8-26).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%201%20-%20Prediction%20motivation%20(8-26).mp4
1 - 2 - What is prediction- (8-39).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%202%20-%20What%20is%20prediction-%20(8-39).mp4
1 - 2 - What is prediction- (8-39).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%202%20-%20What%20is%20prediction-%20(8-39).mp4
1 - 3 - Relative importance of steps (9-45).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%203%20-%20Relative%20importance%20of%20steps%20(9-45).mp4
1 - 3 - Relative importance of steps (9-45).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%203%20-%20Relative%20importance%20of%20steps%20(9-45).mp4
1 - 4 - In and out of sample errors (6-57).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%204%20-%20In%20and%20out%20of%20sample%20errors%20(6-57).mp4
1 - 4 - In and out of sample errors (6-57).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%204%20-%20In%20and%20out%20of%20sample%20errors%20(6-57).mp4
1 - 5 - Prediction study design (9-05).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%205%20-%20Prediction%20study%20design%20(9-05).mp4
1 - 5 - Prediction study design (9-05).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%205%20-%20Prediction%20study%20design%20(9-05).mp4
1 - 6 - Types of errors (10-35).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%206%20-%20Types%20of%20errors%20(10-35).mp4
1 - 6 - Types of errors (10-35).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%206%20-%20Types%20of%20errors%20(10-35).mp4
1 - 7 - Receiver Operating Characteristic (5-03).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%207%20-%20Receiver%20Operating%20Characteristic%20(5-03).mp4
1 - 7 - Receiver Operating Characteristic (5-03).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%207%20-%20Receiver%20Operating%20Characteristic%20(5-03).mp4
1 - 8 - Cross validation (8-20).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%208%20-%20Cross%20validation%20(8-20).mp4
1 - 8 - Cross validation (8-20).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%208%20-%20Cross%20validation%20(8-20).mp4
1 - 9 - What data should you use- (6-01).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%209%20-%20What%20data%20should%20you%20use-%20(6-01).mp4
1 - 9 - What data should you use- (6-01).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/1%20-%209%20-%20What%20data%20should%20you%20use-%20(6-01).mp4
2 - 1 - Caret package (6-16).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%201%20-%20Caret%20package%20(6-16).mp4
2 - 1 - Caret package (6-16).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%201%20-%20Caret%20package%20(6-16).mp4
2 - 2 - Data slicing (5-40).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%202%20-%20Data%20slicing%20(5-40).mp4
2 - 2 - Data slicing (5-40).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%202%20-%20Data%20slicing%20(5-40).mp4
2 - 3 - Training options (7-15).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%203%20-%20Training%20options%20(7-15).mp4
2 - 3 - Training options (7-15).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%203%20-%20Training%20options%20(7-15).mp4
2 - 4 - Plotting predictors (10-39).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%204%20-%20Plotting%20predictors%20(10-39).mp4
2 - 4 - Plotting predictors (10-39).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%204%20-%20Plotting%20predictors%20(10-39).mp4
2 - 5 - Basic preprocessing (10-52).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%205%20-%20Basic%20preprocessing%20(10-52).mp4
2 - 5 - Basic preprocessing (10-52).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%205%20-%20Basic%20preprocessing%20(10-52).mp4
2 - 6 - Covariate creation (17-31).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%206%20-%20Covariate%20creation%20(17-31).mp4
2 - 6 - Covariate creation (17-31).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%206%20-%20Covariate%20creation%20(17-31).mp4
2 - 7 - Preprocessing with principal components analysis (14-07).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%207%20-%20Preprocessing%20with%20principal%20components%20analysis%20(14-07).mp4
2 - 7 - Preprocessing with principal components analysis (14-07).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%207%20-%20Preprocessing%20with%20principal%20components%20analysis%20(14-07).mp4
2 - 8 - Predicting with Regression (12-22).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%208%20-%20Predicting%20with%20Regression%20(12-22).mp4
2 - 8 - Predicting with Regression (12-22).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%208%20-%20Predicting%20with%20Regression%20(12-22).mp4
2 - 9 - Predicting with Regression Multiple Covariates (11-12).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%209%20-%20Predicting%20with%20Regression%20Multiple%20Covariates%20(11-12).mp4
2 - 9 - Predicting with Regression Multiple Covariates (11-12).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/2%20-%209%20-%20Predicting%20with%20Regression%20Multiple%20Covariates%20(11-12).mp4
3 - 1 - Predicting with trees (12-51).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/3%20-%201%20-%20Predicting%20with%20trees%20(12-51).mp4
3 - 1 - Predicting with trees (12-51).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/3%20-%201%20-%20Predicting%20with%20trees%20(12-51).mp4
3 - 2 - Bagging (9-13).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/3%20-%202%20-%20Bagging%20(9-13).mp4
3 - 2 - Bagging (9-13).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/3%20-%202%20-%20Bagging%20(9-13).mp4
3 - 3 - Random Forests (6-49).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/3%20-%203%20-%20Random%20Forests%20(6-49).mp4
3 - 3 - Random Forests (6-49).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/3%20-%203%20-%20Random%20Forests%20(6-49).mp4
3 - 4 - Boosting (7-08).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/3%20-%204%20-%20Boosting%20(7-08).mp4
3 - 4 - Boosting (7-08).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/3%20-%204%20-%20Boosting%20(7-08).mp4
3 - 5 - Model Based Prediction (11-39).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/3%20-%205%20-%20Model%20Based%20Prediction%20(11-39).mp4
3 - 5 - Model Based Prediction (11-39).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/3%20-%205%20-%20Model%20Based%20Prediction%20(11-39).mp4
4 - 1 - Regularized regression (13-20).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/4%20-%201%20-%20Regularized%20regression%20(13-20).mp4
4 - 1 - Regularized regression (13-20).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/4%20-%201%20-%20Regularized%20regression%20(13-20).mp4
4 - 2 - Combining predictors (7-11).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/4%20-%202%20-%20Combining%20predictors%20(7-11).mp4
4 - 2 - Combining predictors (7-11).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/4%20-%202%20-%20Combining%20predictors%20(7-11).mp4
4 - 3 - Forecasting.mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/4%20-%203%20-%20Forecasting.mp4
4 - 3 - Forecasting.mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/4%20-%203%20-%20Forecasting.mp4
4 - 4 - Unsupervised Prediction (4-24).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/4%20-%204%20-%20Unsupervised%20Prediction%20(4-24).mp4
4 - 4 - Unsupervised Prediction (4-24).mp4https://github.com/GooseCoder/PracticalMachineLearning/blob/master/VideoLectures/4%20-%204%20-%20Unsupervised%20Prediction%20(4-24).mp4
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