In this repository, I have tried to predict house prices using a neural network model in Keras.

This project uses a customized housing price data with the following features:
Number of rows: 5000
Number of columns :7
Features:

• Year of sale of the house
• Age of the house at the time of sale
• Distance from the city centre
• Number of stores in the locality
• Latitude
• Longitude

To predict the housing sale price of a particular house using Neural Networks in Keras and make use of "EarlyStopping" and "History Callback" feature in neural networks

The model that I have implemented has the following features:

• Dense Hidden Layer with 10 neurons (activation = relu)
• Dense Hidden Layer with 50 neurons (activation = relu)
• Dense Hidden Layer with 30 neurons (activation = relu)
• Optimizer = "Adam"
• Loss = Mean Squared Error

For this model, I have tracked the validation loss as a parameter for which no more training is required at a patience level of 5 epochs