Data mining and pattern recognition form the cornerstone of modern data science by enabling the extraction of meaningful information from vast and complex data sets. These techniques integrate ...

Data mining is a process which finds useful patterns from large amount of data. It is a powerful new technology with great potential to help companies focus on the most important information in their ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

This course Introduces basic data mining concepts and techniques for discovering interesting patterns hidden in large-scale data sets, focusing on issues relating to effectiveness and efficiency.

Data mining has its origins in conventional artificial intelligence, machine learning, statistics, and database technologies, so it has much of its terminology and concepts derived from these ...

Data mining isn’t just techno-speak for messing around with a lot of data. Data mining doesn’t give you supernatural powers, either. Data mining is a specific way to use specific kinds of math. It’s ...

The exponentially increasing amounts of data being generated each year make getting useful information from that data more and more critical. The information frequently is stored in a data warehouse, ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. Newer AI techniques and data mining, which traditionally use machine learning, together can ...

A “Data Mining Research Problem Book” marked “top secret strap 1” has been leaked that details some of the key techniques used by GCHQ to sift through the huge volumes of data it pulls continuously ...

Predictive analytics enables you to develop mathematical models to help you better understand the variables driving success. Predictive analytics relies on formulas that compare past successes and ...

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.