A Machine Learning Project implemented from scratch which involves web scraping, data engineering, exploratory data analysis and machine learning to predict housing prices in New York Tri-State Area.

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.

Housing price prediction using Regularised linear regression

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

Predicting housing prices using Bengaluru house price dataset

Search places get housing price🤑

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.

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.

TensorFlow/Keras examples and notes.

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

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

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.

Housing Prices Data Analysis with Python

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

Modeling the Spatial Distribution of Location Adjustment Parameters.

Hosing sales dashboard of Washington DC made in Tableau

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

Melbourne Housing Analysis using Linear and Lasso Regression

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.