Encoding: converting categorical data into a numerical data

Feature Engineering with Python

Feature Engineering

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

Machine Learning Project

Showcasing data science skills for a dataset provided by State Farm for a coding interview.

Kaggle Project

No description provided.

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.

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) (Done alongside Kaggle ML courses)

Book price dataset analysis and modeling

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

No description provided.

Machine Learning Models

Job-A-thon ML challenge

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

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

Students Placement based on some characteristics.

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

Прогнозирование рыночной стоимости автомобилей

Supervised Learning project from TripleTen

House Price Prediction (Kaggle)

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.

Predicting whether the person is a smoker or not.