Machine learning

What is machine learning?

Machine learning (ML) is a branch of artificial intelligence in which software learns from data rather than following hand-written rules. Instead of a developer coding every instruction, an ML model is trained on examples and discovers the patterns itself, then uses them to make predictions or decisions on new, unseen data.

How machine learning works

An ML workflow usually follows four steps: collect and prepare data, choose a model, train it by letting it adjust to the data, then evaluate and deploy it. The model improves as it sees more relevant, good-quality data.

Main types of machine learning

• Supervised learning: trained on labelled examples (input to known output), e.g. spam detection.
• Unsupervised learning: finds structure in unlabelled data, e.g. customer segmentation.
• Reinforcement learning: learns by trial and error through rewards, e.g. game-playing or robotics.

Machine learning vs AI vs deep learning

Artificial intelligence is the broad goal of making machines act intelligently; machine learning is the main approach to get there; and deep learning is a subset of ML that uses large neural networks, the technology behind modern large language models (LLMs) and image generators.

Machine learning in automation & the web

ML powers recommendation engines, chatbots, search, personalisation and content generation. For businesses, it turns data into automated decisions, from lead scoring to smart internal tools. At BeBranded we connect these AI capabilities to your website and workflows; see our Automation and AI agents services.