A music recommender - making sense of 24 million user plays from 1.6 million unique artists using Apache Spark.

Data applications are like sausages. It is better not to see them being made - Otto von Bismarck

Data science, two words which even the initiated have trouble with explaining to the layperson. There's an old saying that if you can't explain it to your grandmother, you probably do not understand it well enough. That stands very true, especially today in 2016, given the complexities that more often than not plague most intellectual endeavors. Personally my favorite go-to line when I'm on the receiving end is - Please explain to me as you might to a child, or a ...

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Predicting Board Game Reviews using KMeans Clustering & Linear Regression

Board games have been making a comeback lately, and deeper, more strategic boardgames, like Settlers of Catan have become hugely popular. BoardGameGeek is a popular site where these types of board games are discussed and reviewed.

Here we have a dataset that contains 80000 board games and their associated review scores. The data was scraped from BoardGameGeek and compiled into CSV format by Sean Beck.

Let's preview the data and look at some interesting columns.

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Predicting Bike Rentals by Applying Decision Trees & Random Forests

In many cities, there are communal bicycle sharing stations where you can rent bicycles by the hour or by the day. Kind of reminds me how we rent out cloud servers as I write this, haha. Washington, D.C. is one of these cities, and has detailed data available about how many bicycles were rented by hour and by day.

The powerful Hadi Fanaee-T at the University of Porto has compiled this data into a CSV file The file contains 17380 rows, and each row represents the bike rentals in a single hour of a single day. Let's take a closer look at it.

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