Supervised learning is a type of machine learning in which data is fully labeled and algorithms learn to approximate a mapping function well enough that they can accurately predict output variables given new input data. This section contains supervised learning techniques. For example, Support Vector Machine (SVM), is a type of algorithm that is a discriminative classifier formally defined by a separating hyperplane used for regression and classification tasks.
Supervised learning is predicated on the use of well-labeled data. There are a number of companies in the data labeling software industry.
Data labeling software companies
Timeline
Further Resources
NVIDIA Blog: Supervised Vs. Unsupervised Learning
Isha Salian
Web
Supervised and Unsupervised Machine Learning Algorithms
Jason Brownlee
Web