As an Intern at PISE, My boss asked me to develop a machine learning model to predict the prices of real estate properties, So I decided to built one simple linear model which i deployed using streamlit to see how user can have access to it. The program is subdivided into two part,
1. Building the Linear model (a quite good performance)
2. Save the model to be used on streamlit
3. Create a simple api to take input from users, and finally deploy an interface with streamlit.
4. The dependencies used are: *streamlit* and *ngrok* as seen on the jupyter notebook provided in this repo
5. All have been done on google colab
6. The dataset used is available in this link: [here](https://www.kaggle.com/quantbruce/real-estate-price-prediction)
- If you want to train the model again, run the jupyter notebook to ubtain the weights for predictions
- make sure the app.py is in thesame directory as the notebook
- Install all dependencies (
numpy,pandas,matplotlib, streamlit,pyngrok)