Learning Data Science: Sentiment Analysis with Naive Bayes


As we have already seen in former posts simple methods can be surprisingly successful in yielding good results (see e.g Learning Data Science: Predicting Income Brackets or Teach R to read handwritten Digits with just 4 Lines of Code).

If you want to learn how some simple mathematics, known as Naive Bayes, can help you find out the sentiment of texts (in this case movie reviews) read on!
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Learning R: Data Wrangling in Password Hacking Game


Data Scientists know that about 80% of a Data Science project consists of preparing the data so that they can be analyzed. Building Machine Learning models is the fun part that only comes afterwards!

This process is called Data Wrangling (or Data Munging). If you want to use some Base R data wrangling techniques in a fun game to hack a password read on!
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Teach R to see by Borrowing a Brain


It has been an old dream to teach a computer to see, i.e. to hold something in front of a camera and let the computer tell you what it sees. For decades it has been exactly that: a dream – because we as human beings are able to see, we just don’t know how we do it, let alone be precise enough to put it into algorithmic form.

Enter machine learning!
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Data Science on Rails: Analyzing Customer Churn

Customer Relationship Management (CRM) is not only about acquiring new customers but especially about retaining existing ones. That is because acquisition is often much more expensive than retention. In this post, we learn how to analyze the reasons of customer churn (i.e. customers leaving the company). We do this with a very convenient point-and-click interface for doing data science on top of R, so read on!
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