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

An implementation of a symbolic regression model

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

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.

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

Lasso and Inductive Conformal Prediction Algorithm

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.

KMeans Clustering of data using Sklearn library, numpy and Pickle data

Today there are no certain methods by using which we can predict whether there will be rainfall today or not. Even the meteorological department’s prediction fails sometimes. In this project, I learn how to build a machine learning model which can predict whether there will be rainfall today or not based on some atmospheric factors.

Consist of ML projects based on Python along with DataSheets

Create a model that helps choose the region with the highest profit margin.

Model designed to predict premier league games outcomes based on data from the year 1993 - 2023

A diverse dataset comprising various car attributes such as mileage, model year, brand, and more, our predictive model employs to accurately forecast the prices of audi car. From data preprocessing to model training and evaluation, our repository provides code implementation, enabling users to understand and replicate our results seamlessly.

This group project aims to predict the arrest of different types of crime given a specific input (day/ location/etc.) using machine learning models.

Classification of Text from Youtube Comments using BistillBERT alanguage models from Hugginface Transformers

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.