Titanic Project 🚢

A machine learning app to determine the chance of survival on the Titanic based on various features. Try it live at https://share.streamlit.io/sleepypioneer/titanic_survival_model/main/src/app.py

Development 🖥️

This app has been developed with Python 3.8.5 and streamlit using Jupyter notebooks to explore the data and build the model.

Download the data 💾

The data for this project has not been checked into Github, so you will need to download it locally first. You can download the data from Kaggle here (you will need both the test.csv and train.csv) save these files in the directory: /model_in_notebook/data/

Create and activate a virtual environment 🌐

# create the environment
python3.8.5 -m venv venv

# activate it on linux or Mac from this repository
source ../venv/bin/activate

# activate it on windows
venv\Scripts\activate.bat

Install dependencies 🧰

You can install all the necessary dependencies, listed in requirements.txt by running the following command:

pip install -r requirements.txt

Running the app locally 🧊

Now that the virtual environment activated run the following command to run the streamlit app with live reload on save.

# This command needs to be run inside the src/ directory
# To change into the src/ directory
cd src
streamlit run --server.runOnSave=True app.py

This will run the app locally at http://localhost:8501/

To stop the service running use Ctrl c

Exploring the notebooks locally 📘

You can also open the notebooks exploring the data and building the model. To do this follow the instructions in this README

Tests

Deployment

Currently, this app is deployed with Streamlit sharing ❤️