In the real world, many people get cheated by real estate brokers and contract agents with the price of the house. So this will help a lot of people to find the price of houses when they are selling or buying.
- When adding more deep neural networks the validation loss getting reducing, But in my system I can't increase neural networks, for this deeplearning model it's took me 1-2 hour to fit the model.
This DeepLearning model to predict house prices.
- Python3 (Jupyter Notebook)
- Numpy
- Pandas
- tensorflow
- keras
- Data Cleaning
- Sequential Layers
- Fitted model using Train Data
- Saved DeepLearning Model in h5 file format
- Load saved Model
- Clone project
- Create a branch
- Open jupyter_notebook.ipynb
- Make changes in Sequential Layers to reduce validation loss
- Fit model by using Train Data
- Save Model in h5 format
- Create a pull request
