Machine learning using python

Implementation of different regression technique

Machine Learning Algorithms for Cancer Sample Prediction

The project is designed to predict the Air Quality Index of a Mumbai region given climate conditions using a Machine Learning Algorithm. Implemented in an end-to-end manner using Flask framework and Heroku platform.

R Data Mining and ML algo implementations(Learning Basics and notes)

Constructing a linear regression model which may help us predict the happiness score in the 155 countries.

In this project I used different regression algorithms to do regression to predict ticket price. I used Kaggles free GPUs and Machinehack Datasets in this project.

Comparing Ridge and LASSO model to find the best accuracy for Home Price Prediction

Project 2 Group C - Predicting FinTech Bootcamp Graduate Salaries

Developed a sophisticated Regression Model utilizing advanced algorithms like Linear Regression, Random Forest, to forecast Sales for historical sales data for 1,115 Rossmann stores in 7 European countries. Implemented various processing techniques, including Feature Scaling, Outlier Treatment, and Multicollinearity analysis, to improve accuracy.

Predicting house price

Credit risk analysis using the LASSO, Random Forests and the SMOTE technique for balancing

IMDB Reviews Text Categorization Using Machine Learning Classifiers (Logistic Regression, Ridge Regression, Lasso Regression, Elastic Net Regression, KNN)

Machine Learning Regression model For Bike Sharing Demand Prediction

Simple Machine Learning Projects done for a Data Science Course

This repository contains code for predicting the price of mobile phones using regression models. It includes the implementation of various regression techniques such as Random Forest Regression, Decision Tree Regressor, Linear Regression, and Lasso Regression.