A symbolic regression model

Implement model regression linear simple and multiple form scratch and compare it the sklearn model

This model is designed to determine the age of a crab based on its other physical characteristics. Using this model, it is possible to determine the age of a crab through its other data!

Electronic Music Classification ML

Uber Trip Demand Analysis and Prediction using Python and Machine Learning. This project explores trip patterns, peak demand times, and uses models like Random Forest, GBRT, and XGBoost to forecast ride demand.

Cybersecurity threat detection project that analyzes AWS CloudWatch web traffic logs to identify suspicious and anomalous interactions using machine learning models like Isolation Forest, Random Forest, and Neural Networks.

Diabetes Prediction Dataset

Software aimed at real-time prediction of match outcomes for FIRST Tech Challenge using machine learning algorithms.

The Telco Customer Churn dataset, the project involves collecting, cleaning, and analyzing customer data to uncover key factors influencing churn.

A text classification library creating an easy way to interface with Sklearn and build models

Laptop Price Prediction using Machine Learning. This project analyzes laptop specifications like RAM, CPU, storage, and GPU to predict prices using data preprocessing, EDA, and a Linear Regression model.

Using a real-world Telco Churn dataset, this project covers the complete data analysis pipeline — from data cleaning and exploration to model building and evaluation.

Reduce the time that cars spend on the test bench. Work with a dataset representing different permutations of features in a Mercedes-Benz car to predict the time it takes to pass testing. Optimal algorithms will contribute to faster testing, resulting in lower carbon dioxide emissions without reducing Mercedes-Benz’s standards.

Machine Learning Drug Classification

Coca-Cola Stock Analysis & Price Prediction using Python and Machine Learning. This project performs exploratory data analysis (EDA), technical indicator creation, and uses a Random Forest model to forecast future stock prices based on historical market data.

The project “HR Analytics – Employee Attrition Prediction” aims to predict employee attrition based on various work-related factors using the IBM HR Analytics Dataset.

Leverages Logistic Regression to predict credit risk for customers based on the German Credit Data dataset

Titanic - Predicting Survival Using Machine Learning

Reduce the time that cars spend on the test bench. Work with a dataset representing different permutations of features in a Mercedes-Benz car to predict the time it takes to pass testing. Optimal algorithms will contribute to faster testing, resulting in lower carbon dioxide emissions without reducing Mercedes-Benz’s standards.