This project analyzes and preprocesses the Online Retail dataset to uncover insights into customer purchasing behaviors, sales trends, and product performance. It includes data cleaning, exploration, and visualization, with the goal of enhancing understanding of online retail dynamics.

A repository containing machine learning projects and models.

Student Performance Predictor is an end-to-end machine learning project that implements a complete predictive modeling pipeline. It analyzes the impact of demographic, socioeconomic, and academic factors on student mathematics performance, performing data preprocessing, feature engineering, machine learning model & deployment using Flask & Render.

Find interesting analytics with Google Play Store App data in here : https://nbviewer.org/github/GraceJHLee/App-Store-Analytics/blob/main/Google%20Play%20Store%20App%20Analytics.ipynb

Linear Algebra project from TripleTen

Using a insurance data to build a linear regression model , assumption checks, ANOVA , Post-hoc test, Mini=project

A simple linear regression model and CSV parser.

This is a ML (Machine Learning) project for predicting energy consuming by pepole

stock price prediction using machine learning models for short-term forecasting based on historical market data.

This project tackles the classic problem of house price prediction by implementing and comparing three powerful regression models. The objective is to build a reliable predictive tool for real estate valuation and to explore the benefits of regularization in machine learning.

Test various time-series Models to predict future movements in the value of the Japanese yen versus the U.S. dollar.

An end-to-end Machine Learning powered web application that predicts house prices using Linear Regression, built with Django and deployed with an interactive user interface.

In this project we’ll use condominium sales data from all 5 boroughs of New York City to determine how well the size of a condominium (measured in gross square feet) explains/predicts sale price for each individual borough & across New York City as a whole.

End-to-end machine learning project analyzing a European motorbike marketplace dataset, combining exploratory data analysis, data preprocessing, and regression modeling to predict motorbike prices.