Concepts like machine learning and artificial intelligence sound weird and mysterious?
I will accompany you to discover this fascinating world starting from the basics.
So, finally, the technological secrets that permeate our modern daily life will be clearer to you.
Machine learning surrounds us!
You wake up, take some bread and heat it in the microwave, which in a few seconds does its job as expected.
You drive to work and your smartphone recommends you to choose another way because of an accident. Even today you have avoided a dozen insults.
Are you Italian like me? More than a dozen.
After four hours in the office, you spend your lunch break biting a sandwich and scrolling photos on Tinder, who seems to know you better than your best friend.
How do you say? You have never used Tinder?
Of course, my dear, of course. Me neither! BLINK BLINK.
After the break, you spend your time PRODUCTIVELY on the laptop browsing Netflix, which recommends several interesting new titles.
Magic? No, Machine learning!
All these interactions between you and the machines now seem obvious and automatic.
Yet, if you think about it, they have something almost magical. This magic, which is NOT magic, is called machine learning.
Excluding the microwave.
That really works by magic.
What is Machine learning?
Machine learning is basically a branch of artificial intelligence.
More specifically, it explores the study and construction of algorithms that can learn from a set of data and make predictions about them.
In other words, our algorithms will inductively build a model based on samples. It is, therefore, a process closely related to pattern recognition.
In the field of computer science, machine learning is a variant of traditional programming.
It provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
This translates materially into having algorithms that can give interesting information about a set of data, without having to write any specific code.
Instead of writing the code, the data is entered into a generic algorithm and the algorithm generates its own logic based on the data entered.
“Machine learning provides systems the ability to automatically learn and improve from experience without being explicitly programmed.”
A mathematical example to understand Machine learning
To give a small example, traditional programming provides an X input and an f function that processes it giving, as a result, an Y output.
In machine learning we could instead give the computer a series of inputs and the related outputs, asking it to find out which mathematical function connects them.