> For the complete documentation index, see [llms.txt](https://davidjosearaujo.gitbook.io/notes-miect/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://davidjosearaujo.gitbook.io/notes-miect/redes-e-sistemas-autonomos/self-organized-systems-data-learning-and-decisions/machine-learning.md).
# Machine Learning
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#### A pragmatic definition...
Collection of algorithms and statistical models (methods) for machines to carry out automated tasks **based on the observation of inputs and/or outputs of a process**.
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The **goal** of machine learning is to **produce an estimation or a classification** given a set of input values.
We often distinguish:
* **ML method:** the **mechanism to train a model** (neural network, support vector machine, etc).
* **ML model:** an **instance of the method trained** to **replicate** the **behavior** of the target process.
## Types of Learning
### Supervised
The **model is trained with a dataset of the target process**.
When trained for a classification task, the historical dataset should contain the **Ground Truth - the actual class of a given sample**.
### Unsupervised
**Classification or regression does not depend on prior knowledge**.
