This is about Treue Technologies Data science Internship tasks.

This has been a machine learning quest to classify cancer types using gene expression data, utilizing powerful tools and techniques to preprocess, train and evaluate models. The ultimate goal, to save lives through early diagnosis with high accuracy and precision.

Linear Regression Models on Montesinho Forest Fire

This repository explores and compares different regression models for predicting continuous outcomes. This repository includes implementations and evaluations of five key regression models. The primary goal is to demonstrate how each model works, evaluate their performance using R-squared values, and guide users in selecting the best model.

Predicting compressive strength of concrete using machine learning models with featurization and Hyper parameter tuning

It calculates the accuracy score and confusion matrix for a logistic regression model. The dataset is about coupon used or not in an apparel store known as Simmons .

Integrated robust and reliable ML Pipelines for Research and Production environment

Check my projects related to ML feature engineering and modeling.

A dredge function to select the best models through an exhaustive combination of parameters.

A web application that employs machine learning models to provide accurate and instant car price estimations based on various features and specifications.

Multiple Disease Prediction System using Machine Learning.

Machine Learning project based on UCI mushroom dataset

Open Machine Learning course at MIPT

Machine Learning Projects learning and Practicing

This project uses supervised machine learning techniques with multiple regression models to predict CO2 emissions in Canada, it includes data cleaning, encoding, analyzing and visualization to identify patterns, resulting in a model that can make accurate predictions.

Amazon employee data to predict approval/ denial

We have been given historical sales data for 45 stores situated in various regions. Each store comprises multiple departments, and our objective is to forecast sales for each department within these stores.