Supervised Machine Learning

Supervised machine learning is a type of artificial intelligence (AI) used to identify patterns in data. It uses a labeled dataset to learn from and is able to make predictions about unseen data. Supervised machine learning is used in many applications such as medical diagnosis, fraud detection, image recognition and natural language processing. It is capable of accurately detecting complex relationships and can be used to provide more insight into real-world problems. Supervised machine learning is an important and powerful tool in the modern AI space, and is quickly becoming a popular choice for researchers and businesses alike.

← Journal of Big Data Research

Related Articles

9 article(s) found
Analyzing Students’ Opinions about their Learning Environments and Study Approaches with Bayesian Modeling
Full-text HTML Download PDF Download XML
Effect of a Waterproof Device in the Noninvasive Ventilation Circuit on patient-machine Synchronization
Full-text HTML Download PDF Download XML
Appropriate Conservation Machinery for Mungbean Cultivation in the Southern Region of Bangladesh
Full-text HTML Download PDF Download XML
Study of The ID3 and C4.5 Learning Algorithms
Full-text HTML Download PDF Download XML
Statistical Analysis on the Influence of Flipped Classroom Teaching on Students’ Learning Effect During the Coronavirus Disease 2019 Epidemic
Full-text HTML Download PDF Download XML
Critical Review of Teaching and Learning Methodologies for Learners with Special Educational Needs in the 21st Century and Beyond
Full-text HTML Download PDF Download XML
Success Driven: Student Motivation Actions in Teaching and Learning
Full-text HTML Download PDF Download XML
Comparative Study of Deep Learning Techniques for Detecting Corn Plant Leaf Diseases Using Transfer Learning
Full-text HTML Download PDF Download XML
Learning and Memory in an Animal Model of Longevity: The Ames Dwarf Mice
Full-text HTML Download PDF Download XML