by Angela Guess Alex Woodie recently wrote in Datanami, “The traditional approach to mining unstructured data typically involves training machine learning models upon high-quality “gold standard” data that’s been meticulously groomed. But thanks to innovations in deep learning, more insight may be extracted at less cost by training upon larger amounts of raw data, or […]
A Liberal Arts Approach to Data Science
by Angela Guess George Mount recently wrote in Smart Data Collective, “This week I read a great piece by Adam Weinberg, the president of Denison University, on his school’s initiatives to apply a liberal arts approach to data science. This is shocking to most, but why? Let’s diagram this phrase ‘data science’ (English skills!). Data […]
Survey Shows Data Scientists Spend Most of Their Time Cleaning Data
by Angela Guess Gil Press reports in Forbes, “A new survey of data scientists found that they spend most of their time massaging rather than mining or modeling data. Still, most are happy with having the sexiest job of the 21st century. The survey of about 80 data scientists was conducted for the second year […]
Where Traditional Business Intelligence Tools Fall Short
by Angela Guess Sarah Gerweck recently wrote in Information Management, “Traditionally, Business Intelligence leverages only some of the most basic statistical techniques available. BI is still largely using 17th-century statistical techniques: counts, sums, averages and extrema. At most, we might use techniques that were used by Gauss and Galton in the 19th century (e.g., standard […]