In this episode of Pain Points & Pull Requests, Fatimah and Carla discuss their process and findings from working on another Kaggle competition. This time, they tackle how to build a recommendation system to pair potential donors to a project they could be interested in donating to. 

 

Timestamps

1:12 What is a recommendation system?

2:12 Exploratory data analysis

10:26 Content-based recommendation system

12:29 Evaluating recommendation systems

14:47 Collaborative filtering recommendation system

Extra Resources

Donors Choose Kaggle competition

https://www.kaggle.com/donorschoose/io

An introduction to recommendation systems by Google

https://developers.google.com/machine-learning/recommendation

Donors For Good exploratory data analysis

https://www.kaggle.com/fatimahareola/data-exploration-charity-recommendation-system 

Charity donation recommendation system using scikit-learn and tensorflow

https://github.com/CarlaLeal/Charity-Donation-Recommendation-System

TensorFlow Recommenders

https://blog.tensorflow.org/2020/09/introducing-tensorflow-recommenders.html

DataKind

https://www.datakind.org/