Day 16 of 30 days of Data Engineering Series with Projects

Welcome back peeps to Day 16 of Data Engineering Series with Projects!

In this we will cover —

Data Pre-processing

Handling missing values

Data Cleaning

Mean/mode/median Imputation

Hot Deck Imputation

Rescale Data

Binarize Data

Regression Imputation

Stochastic regression imputation

Feature Scaling

Pre-requisite to Day 16 is to complete Day 1–15( link below):

Day 1 : What’s Data Engineering, Why Data Engineering, Data Engineers — ML Engineers — Data Scientists, Purpose and Scope

Day 2 : Complete Python for Data Engineering — Part 1

Day 3 : Complete Advanced Python for Data Engineering — Part 2

Day 4: Techniques to write efficient and Optimized Code

Day 5 : SQL

Day 6 : Advanced SQL

Day 7 : BigQuery and SQL vs NOSQL databases