In my previous post, 5 Principles for Applying Machine Learning Techniques, I reviewed the principles for putting machine learning to work. In this blog, I will present a brief guided tour of the pipeline that translates that theory into action.
Here at Factual we apply machine learning techniques to help us build high quality data sets out of the gnarly mass of data that we gather from everywhere we can find it. To date we have built a collection of high quality datasets in the areas of places (local businesses and other points of interest) and products (starting with consumer packaged goods). In the long term, however, Factual is about perfecting the process of building data regardless of the area, so many of our techniques are domain agnostic. In this post, I cover 5 principles we use when putting machine learning techniques to work.