AI Methods & Techniques

Hyperparameters are settings you configure before training a machine learning model. Think of them like dials on an oven. You set the temperature and cooking time before you start baking. The model can’t adjust these settings itself during training. They…

Model validation and testing are the processes used to evaluate how accurately and reliably an artificial intelligence or machine learning model performs before it’s deployed in production. They ensure that models make trustworthy predictions, generalise well to new data, and…

A context window refers to the amount of text (or tokens) that an AI language model can process and “remember” at one time. It defines how much surrounding information the model considers when generating a response, influencing both accuracy and…

The Cooperative Principle is a theory from linguistics proposed by philosopher H.P. Grice, describing how people naturally cooperate in conversation to achieve effective communication. It suggests that participants typically follow shared rules or “maxims” to make dialogue meaningful, relevant, and…

Ensemble Learning is a technique in machine learning that combines multiple models to improve predictive performance, accuracy, and stability. Instead of relying on a single model, ensemble methods merge the strengths of several to reduce bias, variance, and overfitting. The…

Agentic AI refers to artificial intelligence systems capable of performing tasks proactively with autonomy and purpose, rather than simply responding to direct instructions. These systems use reasoning, planning, and self-directed goals to complete complex workflows without continuous human input. In…