Definition: machine learning

Dating back to the 1950s, machine learning means software that is programmed by example. Early approaches used rules and decision trees, not the neural network architecture employed today that, after being programmed, is trained by reading volumes of data. One of the first machine learning examples was a checkers game from IBM in the mid-1950s, which beat a master checkers player a few years later.

In addition, in the early days, the world's information was not available online. Today's approach is a "deep learning" neural network that is fed billions and trillions of words from the Internet. See neural network, AI training and AI types.

The Deep Learning Neural Network
A "deep learning" model is a neural network with many layers, and the more layers, the "deeper" the learning. For now, transformers are the most advanced neural network architecture (see AI transformer). See deep learning.

Pattern Recognition
Used in a multitude of AI applications, machine learning is essentially learning patterns. As more samples are used and more fine tuning is applied, the final AI model becomes more dependable. See AI training vs. inference.

The Hierarchy

Almost all modern AI systems use machine learning models. Deep learning is the most advanced form because it absorbs larger amounts of data.

Well Said

This is from Techopedia's "The Ultimate Guide to Applying AI in Business."