Fundamental methods and techniques in computer vision, machine learning and image processing. Programming tools, languages and techniques for the application of machine learning methods to analyse ...

ML (Machine learning) models are used to mine inconspicuous information in big data. The model and data quality influence the performance of a machine-learning model. However, it is inefficient to ...

The past decade has witnessed a plethora of works that leverage the power of visualization (VIS) to interpret machine learning (ML) models. The corresponding research topic, VIS4ML, keeps growing at a ...

As machine learning evolves, more variations of machine learning models will be developed and tested on sparse data. Students and professionals using the skills learned in a master’s in business ...

With multiple layers of suppliers, artificial intelligence and big data can help companies get clean and useful information, says Jim Hayden, chief data scientist at Everstream Analytics.

The data lakehouse architecture is leading this change—particularly for machine learning (ML) and advanced analytics—by combining the strengths of both data lakes and data warehouses.

Your businesses could be leveraging predictive analytics and machine learning to help provide a more personalized user experience. By gathering data on how users interact with your site—such as ...

While approaches and capabilities differ, all of these databases allow you to build machine learning models right where your data resides.

Understanding the differences between business intelligence, artificial intelligence, and data analytics can be a challenge to many people. For many business processes, there seems to be so much ...

Utility giant EDF UK wanted to find a way to exploit its disparate treasure troves of data assets and create pioneering services for its customers using up-to-date data analytics and machine ...