Unsupervised Learning: Identify Target Customers

Linear Regression with multiple variables is implemented to predict the prices of houses using the size of the house (in square feet) and the number of rooms as features. Suppose you are selling your house and you want to know what a good market price would be.

A machine learning project on machine failure binary classification and failure type multi-class classification.

Classification of species of Iris Flowers using Machine Learning and classifier comparison

Red wine quality prediction machine learning model.

Calories_Brunt_Prediction

This is the Prediction of the student's Marks based on their Study Hours -SVM-SVR

Machine learning to predict which passengers survived the Titanic shipwreck

The purpose of this project is to develop and compare two machine learning models to detect spam emails. Spam detection is a crucial task in email filtering systems to protect users from unwanted and potentially harmful emails. The project involves using a dataset containing various features extracted from email content.

Normalizes a value according to the specified steps, using feature scaling.

Supervised learning based on census data to predict income to identify potential donors

Using Machine Learning unsupervised learning techniques to see if any similarities exist between customers and use those similarities to segment customers into distinct categories using various clustering techniques

This project shows a guide for improving the accuracy of regression model.

Feature-Scaling

Study feature scaling.

Support Vector Machine Classification model is applied on bank dataset containing 41188 rows and 21 columns. The data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to assess if the product (b…

This is the Salary Prediction of the people of the Baltimore City -SVM-SVR

Linear regression model to predict the price of a car based on its mileage.

About The Boston House Price Prediction project utilizes data science methodologies and machine learning algorithms to provide accurate predictions for housing prices in the Boston area.

Files for Feature Engg, Feature Scaling, Feature Selection, Statistics and Implementation of every Machine Learning Algorithm.