Post by account_disabled on Mar 11, 2024 13:00:42 GMT 7
With the help of examples and simplifications, let's discover the meaning and functioning of Machine Learning (ML): one of the most named and at the same time most mysterious concepts of our time. We will also discover which problems it solves and the relationship with AI and Deep Learning. Alessio Pomaro Alessio Pomaro 11 Jan 2023 •14 min read Machine Learning: How I Would Explain It to a 5 Year Old Machine Learning: How I Would Explain It to a 5 Year Old Let's start with a premise in which we define, with a good dose of simplification, two terms that we hear very often today: Artificial Intelligence (AI) and Machine Learning (ML) . Artificial Intelligence is a branch of computer science that deals with designing machines with typically human characteristics.
For example, machines capable of interpreting the world around them, or India Mobile Number Data capable of making decisions. This is not just intelligence in the sense of " being able to do calculations ", but intelligence in the broadest sense of the term, such as spatial and social intelligence. The key question is: how does a machine develop artificial intelligence? This is a very complex topic, but let's say that one of the most interesting aspects is certainly that of Machine Learning . In a certain sense we can say that machines are trained to find the best solution to a problem by learning from data and their own errors . Fascinating, right!? Let's discover a simplified explanation of the Machine Learning process . So simplified that it could be told to a child.
A simplified explanation of Machine Learning Imagine having to teach a machine to determine whether a banana is ripe or unripe . To do this we have only one tool available, which can provide us with two indications: how yellow the banana is ( color ); how soft the banana is ( texture ). So how do we explain to the machine how to exploit these two indications to give us an answer? We will proceed by training her through examples , or by passing on the experience to her . This is the same principle through which we learn when we are little: our parents show us examples.
For example, machines capable of interpreting the world around them, or India Mobile Number Data capable of making decisions. This is not just intelligence in the sense of " being able to do calculations ", but intelligence in the broadest sense of the term, such as spatial and social intelligence. The key question is: how does a machine develop artificial intelligence? This is a very complex topic, but let's say that one of the most interesting aspects is certainly that of Machine Learning . In a certain sense we can say that machines are trained to find the best solution to a problem by learning from data and their own errors . Fascinating, right!? Let's discover a simplified explanation of the Machine Learning process . So simplified that it could be told to a child.
A simplified explanation of Machine Learning Imagine having to teach a machine to determine whether a banana is ripe or unripe . To do this we have only one tool available, which can provide us with two indications: how yellow the banana is ( color ); how soft the banana is ( texture ). So how do we explain to the machine how to exploit these two indications to give us an answer? We will proceed by training her through examples , or by passing on the experience to her . This is the same principle through which we learn when we are little: our parents show us examples.