Instead of relying on fixed rules, machine learning algorithms identify patterns and make decisions based on the data they receive. This ability to learn from experience makes machine learning particularly useful in various applications.
In traditional programming, developers write specific instructions to solve problems. In contrast, machine learning allows systems to automatically learn from examples and adapt to new information. This difference opens up exciting possibilities for developing intelligent systems capable of performing incredibly complex tasks.
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# Agent Instructions: Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter:
```
GET https://apphp.gitbook.io/artificial-intelligence-with-php/machine-learning/introduction.md?ask=
```
The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
