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!

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

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

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

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

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.

Electronic Music Classification ML

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

Playing with AI in Python. Pandas, nltk & sklearn

Comparing and evaluating various regression algorithms to accurately predict car prices using data from kaggle.

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.

Titanic - Predicting Survival Using Machine Learning

Consist of ML projects based on Python along with DataSheets

We used various techniques to train and evaluate a model based on loan risk. We used a dataset of historical lending activity from a peer-to-peer lending services company to build a model that can identify the creditworthiness of borrowers.

This github repository contains practice assignments on Python !

Classifying the person as male or female based on hairs, forehead size, nose shape, lips shapes, ect. using ML models