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Avoiding False Discoveries: A completely new addition in the second edition is a chapter on how to avoid false discoveries and produce valid results, which is novel among other contemporary textbooks on data mining. It supplements the discussions in the other chapters with a discussion of the statistical concepts ( statistical significance, p- values, false discovery rate, permutation testing.
Big data architecture and patterns, Part 1.
Introduction to big data classification and architecture. How to classify big data into categories.Learn what cognitive computing is, what it has to do with Deep Learning and Big Data analytics, and what features a cognitive computing solution should have.
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