Day-13 End-to-End Project
Day-16 Working with JSON & SQL
Day-17 Fetching Data from API
Day-19 Understanding Data
Day-20 EDA using Univariate Analysis
Day-21 EDA using Bivariate and Multivariate Analysis
Day-24 Feature Scaling - Standardization
Day-25 Feature Scaling - Normalization
Day-26 Encoding Categorical Data - Ordinal Encoding
Day-27 Encoding Categorical Data - One Hot Encoding
Day-28 Column Transformer
Day-29 Machine Learning Pipelines
Day-30 Function Transformer
Day-32 Binning and Binarization
Day-33 Handling Mixed Variables
Day-34 Handling Date and Time Variables
Day-35 Handling Missing Data - Complete Case Analysis
Day-36 Handling Missing Data - Numerical Data
Day-37 Handling Missing Data - Categorical Data
Day-38 Handling Missing Data - Random Sample Imputation
Day-39 Handling Missing Data - KNN Imputer
Day-40 Handling Missing Data - Iterative Imputer
Day-42 Handling Outliers - Z-Score Method
Day-43 Handling Outliers - IQR Method
Day-44 Handling Outliers - Percentile Method
Day-45 Feature Construction
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