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