EDA_and_Feature_Engineering

In this GitHub Repository, I have Make EDA (Exploratory Data Analysis) and Feature Engineering(FE) Handwritten notes With Practical Implementation of EDA & FE :-

Topic Covers in this Repository are :-

1. Core ML Pipeline

2. Statistics

3. Types of Data :- a) Structure Data b) Un-Structure Data c) Semi- Structure Data

4. EDA Analysis :- a) Profile of the Data b) Statistic Analysis c) Graph Based Analysis

5. Pre-Processing of Data

6. Some Steps of Feature Engineering

7. Automated Tools in Python for EDA

8. Ways of Performing Feature Engineering:- a) Missing Value Handle b) Outlier Handle c) Transformation d) Scaling of Data e) Encoding Method f) Imbalanced Dataset Treatment Method.

NOTE:- And Also Done Some Practical Implementation of EDA & FE( Feature Engineering).

Thanks & Regards