In this task, we use restaurant reviews to predict whether they will pass a hygiene inspection or not. This is a supervised machine learning application of text timing.

In this task, we mine Yelp reviews to elaborate a ranking of the most popular dishes according to the customers opinions. Also, we use the reviews to recommend the best restaurants that serve a given dish.

In a previous report, we explored the topics present in a set of restaurant reviews from Yelp. Some of the topics represented types of cuisines. The restaurants listed in the Yelp dataset, are often labeled according to the kind of cuisine that they serve. In this report, we use restaurant reviews to infer relationships among types of cuisines.

In this paper, I present the data of a karate club social network that Zachary used in his study in 1997. I apply the Clauset, Newman, and Moore modularity optimization algorithm for community detection. I find that the result matches exactly the two factions that appeared in the club.

A line chart that shows the evolution of mean annual temperature anomalies from 1880 to 2014. The data is a subset of the NOAA’s GISS Surface Temperature Analysis (GISTEMP). This visualization was made using the R and the packages dygraph and knitr.

This document describes the process used in Ecophytor to select automatically the exponential growth phase in a growth curve.

In this work, we study the public health and economic consequences of severe weather events across USA. In order to do this we have analyzed a dataset provided by the NOAA that includes figures for the number of victims and damage costs caused by different severe weather event types.