How do Machines Learn?

Completely non technical description, a simple place to start from.   Though here I add its not only how do we teach machines, but also how do they apply that teaching.   And how much do we trust how they apply that teaching?  So we trust an electronic calculator or computer to add many  numbers to get the correct results.  But if we ask something like:  Predict future demand for this product.   Despite the amount of training we may have provided,  there is often complex context to be considered, and except in the simplest examples, no exact answer.    Still an imprecise answer can be useful.  (from a conversation yesterday)

Artificial Intelligence: Here’s What You Need To Know To Understand How Machines Learn in 7WData 

Artificial Intelligence: Here’s What You Need To Know To Understand How Machines Learn
From Jeopardy winners and Go masters to infamous advertising-related racial profiling, it would seem we have entered an era in which artificial intelligence developments are rapidly accelerating. But a fully sentient being whose electronic “brain” can fully engage in complex cognitive tasks using fair moral judgement remains, for now, beyond our capabilities.

Unfortunately, current developments are generating a general fear of what artificial intelligence could become in the future. Its representation in recent pop culture shows how cautious – and pessimistic – we are about the technology. The problem with fear is that it can be crippling and, at times, promote ignorance.

Learning the inner workings of artificial intelligence is an antidote to these worries. And this knowledge can facilitate both responsible and carefree engagement.

The core foundation of artificial intelligence is rooted in machine learning, which is an elegant and widely accessible tool. But to understand what machine learning means, we first need to examine how the pros of its potential absolutely outweigh its cons.

Simply put, machine learning refers to teaching computers how to analyse data for solving particular tasks through algorithms. For handwriting recognition, for example, classification algorithms are used to differentiate letters based on someone’s handwriting. Housing data sets, on the other hand, use regression algorithms to estimate in a quantifiable way the selling price of a given property. ... "