Titanic Classification with Flask Deployment

This repository is a Decision Tree Classifier Implementation done with Sklearn and deployment using a Web Based Application in Python with Flask framework.

Using this Repo

1. Clone this repo using git clone https://github.com/kanuarj/TitanicMLandFlaskDeployment.git command.
2. Install necessary requirements using pip install flask pandas scikit-learn command.
3. Change the directory using cd TitanicMLandFlaskDeployment command.
4. Run the project using py app.py and navigate to localhost:5000 in your browser.

The py app.py specifically works for Windows. Use python app.py for other systems.

Understanding the Files in this Repo

model_notebook.ipynb is the Implementation of Decision Tree Classification Model.
titanic_model.py is the Implementation of joblib model.
app.py is the Flask Implementation of the Model.
templates/index.html contains the front end for the Web Application.

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