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A model of ~50K Kindle book reviews, built with data pulled from Amazon via import.io.
Predict CTR on display ads
Titanic survival people
Model trained on concrete compressive strength data
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.
Kiva is a non-profit organization with a mission to connect people through lending to alleviate poverty.
This model works with a data from build.kiva.org to identify the very small percentage of Kiva loan recipients (<2%) who are most likely to default.
Learn more in this blog post.
predicting mobile carrier customer churn
Predicts NBA salary based on recent player statistics and information
Playmate of the Year stats 1957-2012. Bust prediction.
Credits: Based in the Nathany dataset (1960-2007)