Macha
AI Support & Agents

Machine Learning

Definition

Machine learning is a branch of AI in which systems learn patterns from data to make predictions or decisions, rather than following rules a programmer wrote by hand.

Also known as: MLstatistical learning

How it works

Instead of being explicitly programmed with rules, a machine learning model is trained on examples — labeled data for supervised learning, or raw data for unsupervised learning — and adjusts its internal parameters to minimize error. Once trained, it generalizes to new, unseen inputs.

In customer support, machine learning powers tasks like intent classification, sentiment analysis, and ticket routing. The large language models behind modern AI agents are themselves a form of machine learning, trained on vast amounts of text.

Why it matters for support

Machine learning is the foundation under most support automation. It lets systems improve from real-world data — recognizing the intent behind a message, predicting priority, or spotting sentiment — rather than depending on brittle keyword rules that break as language varies.

Frequently asked

What is the difference between machine learning and AI?

AI is the broad goal of making machines behave intelligently; machine learning is one approach to it, where systems learn from data instead of being explicitly programmed.

Is a large language model machine learning?

Yes. Large language models are deep learning systems, a subfield of machine learning, trained on huge text datasets to predict and generate language.

Put these ideas to work

Macha is an AI agent layer that sits on top of the help desk you already run — Zendesk, Freshdesk, Front, Intercom, or Gorgias.

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