/Titanic_ship-streamlit

Machine Learning model, where using titanic ship data and see if is be able to predict if a passager was salved or died. This apply use Machien learning (Random Forest, gassianNB and Logistic Regressión) . Further, using streamlit together to FastApi be able to see the predict result

Primary LanguagePythonApache License 2.0Apache-2.0

Spaceship Titinic/streamlit/Docker

Machine Learning model, where using titanic ship data and see if is be able to predict if a passager was salved or died. This apply use Machien learning (Random Forest, gaussianNB and Logistic Regressión; using libreris like scikit-learn and optuna) . Further, using streamlit together to FastApi be able to see the predict result

Yyou can find out everything about the project spaceship titinic like data base in the next link: https://www.kaggle.com/competitions/spaceship-titanic/data

Sofware and Tools Requeriments

  1. [GitHub Account] (https://github.com)
  2. [VS Code IDE] (http://code.visualstudio.com/)
  3. Stremlit
  4. Python, Pandas, scikit-learn
  5. Docker Installation

System Setup

  1. Lauch docker compose docker compose up -d
  2. Deployment streamlit : streamlit run main.py

Image of Results:

  • image

  • image