Kaggle Titanic Machine Learning

by wyattwang7

GitHub Readme.md

Kaggle Titanic: Machine Learning Modeling and Deployment

This repository builds a machine learning model on Titanic dataset, creates a web app with Flask to predict the probability of survival per passenger, and deploys the app to Heroku.

Quick Look

  • This video will help you get a feel for the app.
    .

  • Also you could try the app yourself by clicking the button below.
    Deploy

Keywords

EDA, custom estimator, tree classifiers, boosting, model persistance, html, flask, deployment on Heroku

Prerequisites

  • Datasets
    Here is the overview of the project.
  • Dependencies
    xgboost==0.90
    Flask==1.1.1
    dill==0.3.0
    numpy==1.16.4
    requests==2.22.0
    pandas==0.25.1
    scikit_learn==0.21.3
    gunicorn==19.9.0

Accomplishment

  • EDA, feature engineering and modeling (Titanic.ipynb)
  • Model deployment (#clone the repository and run locally)
    1. export FLASK_APP=app.py
    2. python -m flask run
    3. Check the link in the terminal