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🌲 / learning AI Data Science and Machine Learning with Python – Hands-On! Chapter 7 Dealing with Real-World Data

c File Name Size files dur q vq aq Vc Ac Fmt Res fps T Date
-001. BiasVariance Tradeoff.mp439909534377.974422844711125h264aacmov1920x108030mp42023-08-23 17:23:08
-002. [Activity] K-Fold Cross-Validation to Avoid Overfitting.mp452557766628.239093669535125h264aacmov1920x108030mp42023-08-23 17:23:11
-003. Data Cleaning and Normalization.mp441194233432.587755761628125h264aacmov1920x108030mp42023-08-23 17:23:18
-004. [Activity] Cleaning Web Log Data.mp478510259658.425034953820125h264aacmov1920x108030mp42023-08-23 17:23:21
-005. Normalizing Numerical Data.mp424384977204.846463952819125h264aacmov1920x108030mp42023-08-23 17:23:23
-006. [Activity] Detecting Outliers.mp426557215383.198912554421125h264aacmov1920x108030mp42023-08-23 17:23:25
-007. Feature Engineering and the Curse of Dimensionality.mp424920009365.551746545412125h264aacmov1920x108030mp42023-08-23 17:23:28
-008. Imputation Techniques for Missing Data.mp431153388470.9239529395125h264aacmov1920x108030mp42023-08-23 17:23:31
-009. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp423047239336.967982547413125h264aacmov1920x108030mp42023-08-23 17:23:32
-010. Binning, Transforming, Encoding, Scaling, and Shuffling.mp430110672473.361995508375125h264aacmov1920x108030mp42023-08-23 17:23:36

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