{"id":26387,"date":"2025-07-08T11:49:38","date_gmt":"2025-07-08T10:49:38","guid":{"rendered":"https:\/\/22hbg.com\/what-is-really-machine-learning\/"},"modified":"2025-09-10T17:07:04","modified_gmt":"2025-09-10T16:07:04","slug":"what-is-really-machine-learning","status":"publish","type":"post","link":"https:\/\/22hbg.com\/en\/what-is-really-machine-learning\/","title":{"rendered":"What is (really) Machine Learning?"},"content":{"rendered":"\n

Machine Learning explained simple<\/h3>\n\n
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Il Machine Learning \u00e8 la branca dell\u2019intelligenza artificiale<\/a> che consente ai computer di apprendere dai dati e migliorare nel tempo senza essere esplicitamente programmati. Significa che un sistema, elaborando dati, diventa in grado di riconoscere schemi, fare previsioni e prendere decisioni sempre pi\u00f9 accurate.<\/p>\n\n

This is not magic, but applied mathematics and-most importantly-computational skills. It is because of the enormous increase in computing power and access to large amounts of data that Machine Learning has now found concrete applications in key sectors: healthcare, marketing, security, industry, media.<\/p>\n\n

How does it work in practice?<\/h3>\n\n

Machine Learning is based on two fundamental elements:<\/p>\n\n

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  1. Data<\/strong>: it is the fuel of the system. They can be numbers, pictures, words, sounds. The more numerous and the better quality they are, the more effective the model will be.<\/li>\n\n\n\n
  2. Mathematical models<\/strong>: are algorithms that learn from data. They are “trained” on initial datasets and then tested on new data. The goal is to generalize correctly, that is, to provide sensible results even on inputs never seen before.<\/li>\n<\/ol>\n\n

    There are various types of learning:<\/p>\n\n