A few weeks ago, I posed a question on Quora about the differences between machine learning and predictive analytics. I was surprised at the number of people who started following the question and actually liked it (although it sounded rhetorical, I was hoping to understand machine learning better). A recent article in Fast Company about The New York Times, of all companies, did a great job of explaining the fundamental value of machine learning.
My interest in machine learning was ignited recently as it has become the hot buzzword in the Bay Area; some have argued if you add machine learning to your PowerPoint you can add a zero to the end your company’s valuation. While that claim is obviously an exaggeration, investors are among the savviest businessmen, so their interest in machine learning shows it is a crucial emerging space.
The article discusses Chris Wiggins, a biologist The New York Times just hired as its Chief Data Scientist. Wiggins’ mandate is to build and lead the Times’ machine learning team. In Fast Company’s interview with Wiggins, it became clear exactly what machine learning is, how it is different than predictive analytics and why it is important.
What is machine learning
According to Wiggins, “Machine learning sits at the intersection of data engineering and mathematical modeling. The thing that makes it different from statistics traditionally, is far more focus on building algorithms.”
Also, while statistics is traditionally focused on explaining data, machine learning is geared to building predictive models. When Netflix or Amazon make product recommendations to you, they are using machine learning to predict what you would be interesting in experiencing. Continue Reading…