7. Dealing with missing values (II)

8. Filling continuous missing values

9. Dealing with other data issues

10. Dealing with stray characters (I)

11. Dealing with stray characters (II)

12. Method chaining

PART 3. Conforming to Statistical Assumptions
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#MODULE9 #FeatureEngineering

1.Data distributions

2.What does your data look like (I)

3.What does your data look like (II)

4.Scaling and transformations

5.Normalization

6.Standardization

7.Log transformation

8.Removing outliers

9.Percentage based outlier removal

10.Statistical outlier removal

11.Scaling and transforming new data

12.Train and testing transformations (I)

13.Train and testing transformations (II)