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On the Hunt for Patterns: from Hippocrates to Supercomputers

Ontotext

These are the so-called supercomputers, led by a smart legion of researchers and practitioners in the fields of data-driven knowledge discovery. Again, the overall aim is to extract knowledge from data and, through algorithms based on artificial intelligence, to assist medical professionals in routine diagnostics processes.

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Data Mining Use Cases

TDAN

Given that the global big data market is forecast to be valued at $103 billion in 2027, it’s worth noticing. “Information is the oil of the 21st century, and analytics is the combustion engine,” says Peter Sondergaard, former Global Head of Research at Gartner. And he has a point. As the amount of data generated […].

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Bridging the Gap Between Industries: The Power of Knowledge Graphs – Part I

Ontotext

By linking data from car sensors and cameras to data from traffic signals, weather forecasts, bus schedules and social media, knowledge graphs can provide a unified view of a city’s transportation system. This can lead to operational cost cutting and improve competitiveness.

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Fundamentals of Data Mining

Data Science 101

Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). As taught in Data Science Dojo’s data science bootcamp , you will have improved prediction and forecasting with respect to your product. Anomaly Detection.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. Using the adap learning algorithm to forecast the onset of diabetes mellitus. Quinlan, J. Programs for machine learning. Morgan Kaufmann Publishers Inc. Everhart, J. Dickson, W. Knowler, W. C., & Johannes, R.