Massachusetts Institute of Technology (MIT) researchers are looking at ways for machine learning to use more data in its decision-making. Health IT Analytics brought this interesting topic to our attention in their article, “Improving Machine Learning With Big Data-Driven Algorithms.”
The term machine learning generally refers to the construction of algorithms that learn through experience. The requirement of learning through experience necessitates data.
Machine learning algorithms have been implemented to predict many things in healthcare, transportation, industry, etc. Data driven models have drawn attention in recent years, and combined with machine learning techniques, these models appear to be more powerful and able to predict without a priori knowledge of the system and have the potential to achieve high accuracy with low computational cost.
Finding concepts takes artificial intelligence (AI) like machine learning to delve through your data to identify and classify concepts and allows you to expand your semantic model to create meaning and relationships.
Data Harmony is Access Innovations’ AI suite of tools that leverage explainable AI for efficient, innovative and precise semantic discovery of new and emerging concepts to help find the information you need when you need it.
Melody K. Smith
Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.
