Show notes
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. Timestamps1:12 What is a recommendation system?2:12 Exploratory data analysis10:26 Content-based recommendation system12:29 Evaluating recommendation systems14:47 Collaborative filtering recommendation systemExtra ResourcesDonors Choose Kaggle competitionhttps://www.kaggle.com/donorschoose/ioAn introduction to recommendation systems by Googlehttps://developers.google.com/machine-learning/recommendationDonors For Good exploratory data analysishttps://www.kaggle.com/fatimahareola/data-exploration-charity-recommendation-system Charity donation recommendation system using scikit-learn and tensorflowhttps://github.com/CarlaLeal/Charity-Donation-Recommendation-SystemTensorFlow Recommendershttps://blog.tensorflow.org/2020/09/introducing-tensorflow-recommenders.htmlDataKindhttps://www.datakind.org/