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Are You Content with Your Organization’s Content Strategy?

Rocket-Powered Data Science

Specifically, in the modern era of massive data collections and exploding content repositories, we can no longer simply rely on keyword searches to be sufficient. One type of implementation of a content strategy that is specific to data collections are data catalogs. Data catalogs are very useful and important.

Strategy 267
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Fundamentals of Data Mining

Data Science 101

This data alone does not make any sense unless it’s identified to be related in some pattern. Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Machine learning provides the technical basis for data mining.

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AI, the Power of Knowledge and the Future Ahead: An Interview with Head of Ontotext’s R&I Milena Yankova

Ontotext

We apply Artificial Intelligence techniques to understand the value locked in this data so we can extract knowledge that can benefit people. Within a large enterprise, there is a huge amount of data accumulated over the years – many decisions have been made and different methods have been tested.

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On the Hunt for Patterns: from Hippocrates to Supercomputers

Ontotext

Ever since Hippocrates founded his school of medicine in ancient Greece some 2,500 years ago, writes Hannah Fry in her book Hello World: Being Human in the Age of Algorithms , what has been fundamental to healthcare (as she calls it “the fight to keep us healthy”) was observation, experimentation and the analysis of data.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

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. If, however, the dataset is imbalanced with a class ratio of 100:1, this means that it contains only 100 examples of the minority class.

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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

For example, article 22 of the General Data Protection Regulation (GDPR) introduces the right of explanation – the power of an individual to demand an explanation on the reasons behind a model-based decision and to challenge the decision if it leads to a negative impact for the individual. According to Fox et al.,

Modeling 139