House Price Prediction
House Price Prediction
House Price Prediction
GROUP MEMBERS
P.PHANEESH (20KN1A4243)
N.SAI SREEDHAR (20KN1A4241)
N.PAVANI (20KN1A4240)
M.VIJAYA ADITYA (20KN1A4236)
OUTLINE
Introduction
Machine learning
Different Machine learning algorithm s
Dataset
Feature engineering
Model training
Model evaluation
Model deployment
Applications
Conclusion
INTRODUCTION
House price prediction is the use of statistical models to forecast the future price of a house. It is a
complex task, as house prices are influenced by a variety of factors, including:
Location
Size
Age
Condition
There are a variety of machine learning algorithms that can be used for
house price prediction. Some of the most popular algorithms include:
Linear regression
Random forests
Gradient boosted trees
Support vector machines
Neural networks
LINEAR REGRESSION
House price prediction models can be used for a variety of purposes, including:
Helping homeowners estimate the value of their home before they sell it
Helping banks and other financial institutions assess the risk of lending money
on a property
CONCLUSION