Lec-6.8 Data Preprocessing Missing Value Imputation (Arif Butt @ Data Science)
1:24 Learning Agenda
2:40 Data Preprocessing and Feature Engineering
3:49 Missing Data and its Types
7:15 Techniques to handle missing data
9:38 Handling missing data using Pandas
11:57 How to Identifying missing values in your dataset?
14:18 Deleting rows/columns containing missing values
18:24 Univariate Imputation of missing values with mean/median/mode
28:16 Check impact of imputation
30:32 Handling missing data using Scikit-Learn's Transformers
35:18 Using sklearn's SimpleImputer
39:23 Using sklearn's ColumnTransformer
44:29 Multivariate Imputation
45:52 Using sklearn's IterativeImputer
53:01 Using sklearn's KNNImputer
email: [email protected], [email protected], [email protected]
Lecture Slides and Resources: http://arifbutt.me
Jupyter notebooks: https://github.com/arifpucit/data-sci...