This repository contains a collection of Jupyter Notebook files for various feature engineering techniques, including missing value handling, encoding, transformation, imbalanced dataset, and outlier detection. Each notebook provides practical examples of methods for handling the corresponding problem.

In this notebook, i show a examples to implement imputation methods for handling missing values.

This repository contains one of the pre-requisite notebooks for my internship as a Data Analyst at Technocolabs. It includes some of the micro-courses from kaggle.

A classification approach to the machine learning Titanic survival challenge on Kaggle.Data visualisation, data preprocessing and different algorithms are tested and explained in form of Jupyter Notebooks

notebooks tutorial data preparation

Data Preprocessing for Numeric features (Jupyter Notebook)

Data preprocessing is a data mining technique that involves transforming raw data into an understandable format.