Machine Learning Times
Machine Learning Times
Climate Tech Needs Machine Learning, Says PAW Climate Conference Chair
  Straight from the horse’s mouth – the founding...
Predictive Policing: Six Ethical Predicaments
  Originally published in KDNuggets. This article is based...
Measuring Invisible Treatment Effects with Uplift Analysis
  Models make predictions by identifying consistent correlations in...
Machine Learning: Business Leaders Must Take an Enlightening Look Under Its Hood (New Training Program)
  In this article, I identify unmet learner needs...

2 years ago
Data Reliability and Analytic Validity for Non-Dummies

 There is not much attention paid these days to data reliability and validity (DR&V). Many data-scientific practitioners, especially those in Computer Science-IT Data Science (CS-IT Data Science),  don’t get what the terms mean, especially for DR&AV work they might need to do routinely that they do not do at all. After all, we’ve got Big Data. And ultimately, “‘bigness’ mitigates whatever may be wrong with data that might bias findings from analytical operations on it, right? Maybe not. The statement is similar to other claims of CS-IT Data Science “evangelists,” such as “no need for statistics (i.e., ‘not

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