Data mining is more about process than it is about clever algorithms. When the process is not well understood, all the clever techniques and algorithms can get applied to the wrong data, in the ...

The on-campus Master of Science in Data Science program focuses on developing knowledge and skills in interdisciplinary and collaborative data science competencies including statistical analysis, data ...

Specialization: Data Science Foundations: Data Structures and Algorithms Instructor: Sriram Sankaranarayanan, Assistant Professor Prior knowledge needed: Mathematical Background: We expect that the ...

MarketingProfs analyzes the nine most common data mining techniques used in predictive analytics, giving marketers a better way to drive success.

These Algorithms Are Hunting for an EV Battery Mother Lode AI trained on reams of geological data can indicate where to dig in search of metals crucial to electric cars and other green technology.

Algorithms, machine learning and artificial intelligence each play a crucial role in optimizing your hiring processes and keeping you competitive in the talent market.

So if race is disproportionately (but not explicitly) represented in the data fed to a data-mining algorithm, the algorithm can infer race and use race indirectly to make an ultimate decision.

With Google’s new Correlate system, companies have a powerful (and, free!) new data-mining tool on their hands. Let us imagine the ways in which we’ll use it. You can use Google’s algorithms ...