Machine Learning explained simple
Il Machine Learning è la branca dell’intelligenza artificiale 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 più accurate.
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.
How does it work in practice?
Machine Learning is based on two fundamental elements:
- Data: 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.
- Mathematical models: 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.
There are various types of learning:
- Supervised: the system learns from already labeled examples (e.g., “this is a dog, this is not”).
- Unsupervised: the system independently looks for correlations and patterns in the data.
- By reinforcement: the system learns through trial, error and reward (like a robot learning to walk).
Why is it important for companies?
Machine Learning is the key to automate, optimize and predict. It can:
- Improving the customer experience through intelligent recommendations;
- Identify anomalies and fraud in real time;
- Optimize energy and logistics costs;
- predicting market trends;
- Improve product quality through predictive analytics.
At 22HBG, we believe that true innovation is not technology for its own sake, but its concrete application in business processes. Our team integrates Machine Learning models within control platforms, mobile apps, broadcast systems and R&D projects. Our approach is modular, measurable, and fast: in 100 days we turn an idea into a testable MVP.
Want to find out if Machine Learning can improve your business? Contact us for a free evaluation.