Introducing ML
ML is based on the idea of providing computers with a large amount of input data, together with the corresponding correct answers or labels, and allowing them to learn from this data, identifying patterns, relationships, and regularities within them. Unlike traditional programming approaches, in which computers follow precise instructions to perform specific tasks, ML allows machines to independently learn from data and make decisions based on statistical models and predictions.
One of the key concepts of ML is the ability to generalize. This means that a model trained on information in the training dataset should be able to make accurate predictions about new data that it has never seen before. This allows ML to be applied across a wide range of domains.
How to define ML
To better understand the basic concepts of ML, we can start from the definitions formulated by the pioneers in this field. According to Arthur L. Samuel (1959) – “ML is a field...
