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1. datasets datasets Public

   Datasets that I generally use for trainings, workshops

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2. Differenct-ways-of-Graphical-Representation-of-Missing-Data Differenct-ways-of-Graphical-Representation-of-Missing-Data Public

3. Automoblie-Insurance-Claim---EDA-Statistical-Tests-and-Model-Fitting Automoblie-Insurance-Claim---EDA-Statistical-Tests-and-Model-Fitting Public

4. -Kaggle-Dataset---House-Price-In-depth-analysis-and-Imputation-of-Missing-values -Kaggle-Dataset---House-Price-In-depth-analysis-and-Imputation-of-Missing-values Public

5. 120-Change-in-Avg-Temperature-USA-Map-Plot 120-Change-in-Avg-Temperature-USA-Map-Plot Public

6. Classification-problem-and-Model-selection-by-comparing-Confusion-Matrix-ROC-AUC-and-Gain-Chart Classification-problem-and-Model-selection-by-comparing-Confusion-Matrix-ROC-AUC-and-Gain-Chart Public

   The main purpose of this documentation is to Evaluate different models for binary classification and compare them using Confusion Matrix, ROC, AUC and Gain Chart and select the best model.