Dataset of ~50K Kindle book reviews, all containing a description from that book.

data on flavor of 86 single malt scotch whiskies

Kiva is a non-profit organization with a mission to connect people through lending to alleviate poverty.

Source:

Loans from a snapshot at build.kiva.org. A Python script was used to process the JSON files that were downloaded from the snapshot, resulting in a .csv with most pertinent data fields.

Learn more in this blog post.

dataset of web pages from stumbleupon

Model with word counts for about 47,000 text documents, of which roughly 32,000 are novels, 7,500 are supreme court opinions, and 7,500 are webpages from universities. The features are word counts for the 3000 top words by TF*IDF, with stopwords removed.

The novels are from Project GutenbergFDSys, the supreme court cases from FDSys, and the web pages from web->KB.

The dataset on the distinction between good and bad connections (intrusions was part of the data created for The Third International Knowledge Discovery and Data Mining Tools Competition, which was held in conjunction with KDD-99 The Fifth International Conference on Knowledge Discovery and Data Mining.

This is an example for CleverTask

Full dataset of ratings for ~58,000 Kindle titles.

Data pulled from Amazon via import.io.

A mock dataset and predictive model to determine likely churn for a freemium game.