XAI/MLI solution for Kaggle use case using Python.
Machine learning solutions have traditionally been backboxes.
Important to have accountability of such algorithms since in some cases they can be used to make potentially life-changing decisions.
In this project, we have explored the domain of Crowdfunding of projects, specifically "why not every project is able to completely reach their target goal of raising capital".
We have used machine learning explainability techniques to answer the key questions related to the success (or failure) of any crowdfunding project.
Dataset is collected from Kaggle.
Original data collected from Kickstarter Platform
Explainable AI methods used are:
