Machine Learning Times
Machine Learning Times
Podcast: Four Things the Machine Learning Industry Must Learn from Self-Driving Cars
    Welcome to the next episode of The Machine...
A Refresher on Continuous Versus Discrete Input Variables
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Podcast: Why Deep Learning Could Expedite the Next AI Winter
  Welcome to the next episode of The Machine Learning...
PAW Preview Video: Evan Wimpey, Director of Strategic Analytics at Elder Research
 In anticipation of his upcoming presentation at Deep Learning...

4 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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