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Self-Service BI vs Traditional BI: What’s Next?

Alation

Historian Richard Millar Devens first used the term to describe the machinations of banker Sir Henry Furnese, who collected information and acted on it quickly to outsmart his competition. Today, the term describes that same activity, but on a much larger scale, as organizations race to collect, analyze, and act on data first.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? One challenge in applying data science is to identify pertinent business issues.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

Further, imbalanced data exacerbates problems arising from the curse of dimensionality often found in such biological data. Insufficient training data in the minority class — In domains where data collection is expensive, a dataset containing 10,000 examples is typically considered to be fairly large. 1998) and others).