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New “exciting techniques” series of articles.

I am starting a new “exciting techniques” series of articles on the Win-Vector blog. The primary purpose of the Win-Vector blog remains identifying and describing needs, but I am starting a new sub-series of articles about techniques.

Occasionally each of us is asked “what are some things you are excited about?” It is an exciting question, which I never really feel free to actually answer. The reason is that this is usually asked within an obvious context. It would be naive not to recognize that the question is usually really about something specific. In my case the context is usually data handling and storage (an important platform that my work stands on) . Usually I give some weak answer about the quick utility of MapReduce or the promise of column oriented or streaming databases.

Most of the the things I am deeply excited about (limiting myself down to technology to avoid issues like family, charity work or politics) are techniques not products. I would like to give myself the opportunity to mention some of them here.

I am going to be a bit broad in my interpretation of the word “technology.” One dictionary definition of technology is: “the application of scientific knowledge for practical purposes.” I am going to emphasize the “knowledge” portion (ideas, techniques) as being the true core of technology and ignore the artifacts (like databases, web servers or Macbook Pros). This is a matter of taste; I find the ideas much more exciting than the artifacts.

To write about some of these exciting things I am going to try to split the articles on the Win-Vector blog into some more categories. The main stream of articles will be articles about applications. Even identifying how different industries can use mathematical and statistical methods is a very big and a very important task. The most important problem remains correctly identifying needs.

However, I am also very interested in writing about the techniques. Unfortunately, articles about techniques are a bit more esoteric and may not be as useful to my intended audience as application articles. So I will tag these articles as “techniques” to try and segregate them a bit.

Categories: Administrativia


Data Scientist and trainer at Win Vector LLC. One of the authors of Practical Data Science with R.

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