kaggle-titanic-practice

Practicing some data science... Status: in-progress

Plan

• Use titanic kaggle dataset
• use PyCaret (autoMl, model validation)
• SHAP to explain model output? SHAP
• Submission in the kaggle platform
• Docker and/or binder to facilitate deployment

Current score

Score: 0.77033 Leaderboard: 9090

Welcome! Here is some of the information and subject available in the analysis:

• Jupyter folder
  • 01_EDA -> exploratory analysis with first assumptions
    • TO DOs and versioning
  • 02_Process -> jupyter used to format and prepare file to submit

To start playing with this analysis, there are two things you need to do:

IN-PROGRESS

Historic/Versioning

Version	Score	Leaderboard	File
v1	0.76555	9557	submission-12-11-2022.csv
v2	0.77033	9090	submission-12-12-2022.csv

Here are some ideas to contribute if you want (and also my TO DO list for this project):

IN-PROGRESS