Machine learning (ML) can provide unique analytical insights, as well as help automate some operational and decision-making processes more efficiently and effectively than non-ML alternatives. However, ML is also among the buzziest of buzzwords, and many are overselling and overs ...Show more
Machine Learning is Label Making
Label Making. That is my simple two-word definition of Machine Learning. Machine Learning is Label Making. ML is LM. Especially supervised machine learning, which creates either numerical labels (using regression algorithms) to make predictions about a continuous data value (such ...Show more
Cloudy with a Chance of Data Analytics
Based on one of my presentations, this episode provides a five-part vendor-neutral framework for evaluating the critical capabilities of a cloud data analytics solution: Deploy, Store, Optimize, Analyze, Govern. This episode is sponsored by: Vertica.com Extended Show Notes: ocdqb ...Show more
Big Data Quality, Then and Now
A decade ago, just before the beginning of the data science hype cycle was the big data hype cycle. At that time I had the privilege of sitting down with Ph.D. Statistician Dr. Thomas C. Redman (aka the “Data Doc”). We discussed whether data quality matters less in larger data se ...Show more
Three Questions for Data Analytics
Before you get started on any data analytics effort, you need to have at least preliminary answers to three questions: (1) What problem are we trying to solve?, (2) What data can we apply to that problem?, and (3) What analytical techniques can we apply to that data? This episode ...Show more