Machine Learning

Machine learning is the field of knowledge upon which modern artificial intelligence systems are built.

As the name might have hinted, machine learning is, at its core, the construction of methods in which computers can recursively educate and advance their comprehension of certain subjects.

Based on neural networks that replicate human thought processes, ML is an aggregation of complex algorithms that can distill abstract principles into tangible mathematical formulas. Concepts such as linear regression, clustering, and random forest structuring are examples of decision-making techniques that are utilized to make learning possible.

Depending on who you ask, there are three general classes of learning models: Supervised, Unsupervised, and semi-supervised, each containing a multitude of hybrid alternative sub-models (reinforcement, temporal, etc.) within them.

MAGA leverages all of the leading open standards in machine learning to optimize its model’s aptitude to evolve alongside ingesting new data.