Housing Prices Data Analysis with Python

This project uses deep learning techniques to predict median housing prices in the Boston area using the Boston Housing dataset. The model employs TensorFlow, Keras, and Numpy, with a mean squared error loss function and Adam optimization algorithm. The results show high accuracy.

Modeling the Spatial Distribution of Location Adjustment Parameters for the Finance and Taxation Bureau, Tainan City Government in December 2022.

This project enables figuring out the key features that determine the sales price of houses. The resulting Web App helps real estate developers, individual buyers, and banks seek the best area in King County to develop new apartment buildings or make purchases.

Hosing sales dashboard of Washington DC made in Tableau

Advanced-Regression-using-House-Price-Prediction-dataset

TensorFlow/Keras examples and notes.

Melbourne Housing Analysis using Linear and Lasso Regression

Predict House Prices : Embark on a predictive journey using single-variable linear regression. Explore relationships between house features and prices.

Provided valuable insights into the predictive performance of different modeling methodologies for housing price prediction in Boston. It suggests that a combination of linear and non-linear models can be effective and lays the foundation for further research and practical applications in this domain.

My entry for the house prices competition, with a Kaggle score of 0.15537 using elastic net

Predicting housing prices with machine learning regression models. This project implements Linear Regression, Random Forest, and Decision Tree models for accurate predictions.

Attempts at the famous Kaggle housing price prediction competition: in R

Prediction of "Dragon Real State" will be here!!!

We are required to build a regression model using regularisation in order to predict the actual value of the prospective properties and decide whether to invest in them or not. The company wants to know: 1. Which variables are significant in predicting the price of a house, and 2. How well those variables describe the price of a house.

Search places get housing price🤑

The goal is to build a regression model to forecast the price of houses.

Predicting housing prices using Bengaluru house price dataset

This notebook explores the housing dataset from Kaggle to predict Sales Prices of housing using advanced regression techniques such as feature engineering and gradient boosting.

A machine learning project to predict the housing price based on Kaggle Housing Prices Competition