Linear Regression

Basic Projects on Machine Learning Algorithm

Implementation of Machine Learning Algorithms

This repository stores implementations to various projects implementing Machine Learning Algorithms

Written and test in python

1. Linear Regression Algorithm : Linear regression analysis is used to predict the value of a variable based on the value of another variable. The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable's value is called the independent variable.

   For implementing this algorithm I have used hypothetical Dataset , you can also download and use dataset from kaggle (https://www.kaggle.com/)
   
   
   Project Details:
   
   In this project my main tasks was to predict housing prices for regions in the USA. So I have  created a model 
      that allows  to put in a few features of a house and returns back an estimate of what the house would sell for.
   
    I have decided that Linear Regression might be a good path to solve this problem!
   
    Dataset name :USA_Housing.csv.
   
    The data contains the following columns:
   
    1.'Avg. Area Income': Avg. Income of residents of the city house is located in.
    2.'Avg. Area House Age': Avg Age of Houses in same city
    3.'Avg. Area Number of Rooms': Avg Number of Rooms for Houses in same city
    4.'Avg. Area Number of Bedrooms': Avg Number of Bedrooms for Houses in same city
    5.'Area Population': Population of city house is located in
    6. 'Price': Price that the house sold at
    7. 'Address': Address for the house