Member-only story
AI — Machine Learning — Learn It Visually
I created this tutorial as an entry-level piece on Artificial Intelligence.
Any new subject must be presented in language matching the learner’s level of skill at that time. So don’t expect crazy math formulas just yet.
In particular we’ll take a look at Machine Learning aka Deep Learning.
The depth of a Neural Network is determined by number of input layers.
Machine Learning algorithms weigh the likelihood of a particular data set against a specific pattern.
Thinking In Ranges
Neurons in your brain are definitely not digital, but they resemble binary logic as either on or off state. But in software, we use a range of values instead.
The result of a calculation cycle in an AI operation is a precision estimate in the range between 0.0–1.0. Ultimately — an output value is produced based on how well input data matches a specific pattern with 1.0 being 100% match (You rarely reach that but 0.95–0.97 is good.)
This pattern is usually trained before meaningful results can be produced. More on this a bit later in this tutorial. But first, here’s ML at its basic.
It all begins with neural networks — a software imitation of the physical structure of the neurons in a brain.