Home Price Prediction using TensorFlow A machine learning project that predicts home prices using a neural network built with TensorFlow and Keras.
This repository contains code for training and deploying a TensorFlow model that predicts house prices based on various features like square footage, number of bedrooms, location, and proven variables for market trends. The project demonstrates data preprocessing, model building, training, and evaluation steps necessary for a neural network problem in machine learning.
Features Neural network model built with TensorFlow and Keras Training scripts with customizable hyperparameters Model evaluation and performance metrics Colab for interactive exploration Variables Bedrooms Bathrooms Living rooms Zip code Z-score for avg. price Property Sub Type Property Condition at Sale Roof value based on type Square feet Closing Price Closing Price per Sqft Flooring Value based on type Close Date Close Month Mortgage Rate at time of sale Local Unemployment Rate at time of sale Natl Consumer sentiment at time of sale Texas Leading Index at time of sale