Machine Learning

What’s machine learning? It depends on who you ask

Data scientists are professionals who use the most appropriate tools and methodologies to get their jobs done. The best data scientists avail themselves of the complete set of knowledge- and pattern-discovery approaches that involve statistical analysis.
How should we refer to the sum total of data science techniques? Often, they are lumped under the term “advanced analytics.” This phrase is deliberately vague in that it is intended as a catch-all for everything from statistical analysis and data mining to predictive modeling, natural language processing, support vector machines, and so on.
In the popular mind, most of this scope is known as “data mining,” often with a pejorative spin that focuses on privacy violation and surveillance applications. To my mind, that’s a bit like calling every species of bird a “vulture.” The reason is that data mining is applied to structured data only and typically involves specific techniques, such as regression analysis and decision trees, that are not typically used when the content being analyzed is unstructured.
Increasingly, the term “machine learning” is also beginning to acquire a catch-all status. Or, at the very least, machine learning has become a convenient handle that today’s data scientists use to refer to the wide range of leading-edge techniques for automating knowledge and pattern discovery from fresh data, much of it unstructured. People’s working definitions of machine learning seem to be creeping into broader, vaguer territory.

Leave a Comment

Your email address will not be published.

You may also like

Crayon Yoda

Pin It on Pinterest