shrutipandit707 / house-nn-keras

House Price Prediction System with Neural Networks using Keras

In this case study, we are attempting to solve a real world business problem using with Neural Networks using Keras techniques.We are understanding and solving a House Price Prediction problem in Real Estate Domain.We will be checking how data can be used effectively to solve business problems like House Price Prediction Problem.The problem statement that we will be working on is to predict the house sales in a particular location and understand which factors are responsible for higher property value.

Table of Contents

• General Info
• Technologies Used
• Conclusions
• Acknowledgements

General Information

• Provide general information about your project here.

We will be using with Neural Networks using Keras techniques for House Price Prediction System.

• What is the background of your project?

In this case study, we are attempting to solve a real world business problem using with Neural Networks using Keras techniques. We will be understanding and solving a House Price Prediction problem in Real Estate Domain.We will be checking how data can be used effectively to solve business problems like House Price Prediction Problem.The problem statement that we will be working on is to predict the house sales in a particular location and understand which factors are responsible for higher property value.

• Business Problem Statement:

House price prediction is an important concept in the real estate industry. Thus, many researchers from differentfields are interested in developing a regression model for the house price to obtain an accurate prediction and explore the factors affecting the house price. In this study, we aim to develop an accurate regression model using tree-based algorithms and explain the type of information which has an impact on the houseprice. For this purpose, we use the Ames House Price datasetbeing available on Kaggle.

• What is the dataset that is being used?

In this dataset we have to predict the sales price of houses in King County, Seattle. It includes homes sold between May 2014 and May 2015. Before doing anything we should first know about the dataset what it contains what are its features and what is the structure of data.

The dataset cantains 20 house features plus the price, along with 21613 observations.

Conclusions

• We have applied with Neural Networks using Keras techniques approach for House Price Prediction Problem.

Apart from that, your valuable suggestions for further improvement and optimization are always welcome from my side do comment !!

Technologies Used

• Python - version 3.6.9
• Numpy - version 1.21.5
• Pandas - version 1.3.5
• Seaborn - version 0.11.2

Acknowledgements

Give credit here.

• This project was inspired by Upgrad.
• This project was based on Upgrad's Tutorial.

Contact

Created by [@shrutipandit707] - feel free to contact us!