Encoding: converting categorical data into a numerical data

Feature Engineering

Feature Engineering with Python

This repository is totally focused on Feature Engineering Concepts in detail, I hope you'll find it helpful.

Machine Learning Project

Прогнозирование рыночной стоимости автомобилей

Focus on selecting datasets suitable for a machine learning experiment, with an emphasis on data cleaning, encoding, and transformation steps necessary to prepare the data.

[Modeling] Project in 2022 - Simple Model of important factors in the incidence of heart disease and prediction model

Data Cleaning and Data Visualization with python libraries like numpy , pandas, sklean,seaborn, matplotlib-pyplot

Book price dataset analysis and modeling

Machine Learning Models

Ordinal Encoding - Label Encoding

Job-A-thon ML challenge

Feature engineering or feature extraction or feature discovery is the process of extracting features from raw data.

Classification of an imbalanced dataset using SMOTE oversampling technique and ML Algorithms - KNN , XGBoost and Naive Bayes classifier

Students Placement based on some characteristics.

Data preprocessing is a data mining technique that is used to transform the raw data into a useful and efficient format.

A machine learning model to accurately predict house prices based on various features such as quality, size, and location, utilizing Random Forest and XGBoost algorithms (Python)

Why do employees leave? This project first compares the predictive performance of three different models, then uses the best model to help reveal the top contributing factors.