an attempt at making neural networks from scratch.

applying Linear Regression (Simple and Multiple), Polynomial Regression, and Logistic Regression on real-world datasets.

A Regression project aiming to forecast the expenses of individuals within an insurance company where we could then decide whether to charge them a premium package or not.

Regression for Coffee dataset in the US market using R and Python

Bu proje, çoklu doğrusal regresyon kullanılarak balık cins, uzunluk(1,2,3), yükseklik ve genişlik bilgilerine göre ağırlık tahmini yapmaktadır. Veri ön işleme, Backward Elimination ile öznitelik seçimi, model değerlendirme ve Flask tabanlı web arayüzü uygulanmıştır.

Uncover customer churn patterns in telecom data. Utilizing logistic regression, we predict churn and assess model performance. The README guides users through dataset overview and steps. Find detailed insights in the accompanying presentation.

ML-powered Streamlit app to predict student academic performance using regression models