I recently came across the thoughtful article “On Moving from Statistics to Machine Learning, the Final Stage of Grief”. It makes some good points, and is worth the read. However, it also reminded me of the unexamined claim “data science is statistics done wrong.” Frankly this is not the case, […]
In our previous post in this series, we introduced sessionization, or converting log data into a form that’s suitable for analysis. We looked at basic considerations, like dealing with time, choosing an appropriate dataset for training models, and choosing appropriate (and achievable) business goals. In that previous example, we sessionized […]
When we teach data science we emphasize the data scientist’s responsibility to transform available data from multiple systems of record into a wide or denormalized form. In such a “ready to analyze” form each individual example gets a row of data and every fact about the example is a column. […]