Page 83 - AI & Machine Learning for Beginners: A Guided Workbook

Reinforcement Learning – A machine learning approach where

an AI agent learns through trial and error, receiving rewards or
penalties for actions taken.

Supervised Learning – An ML approach where the model is

trained using labeled data, enabling it to learn patterns based on
input-output pairs.

Transfer Learning – The practice of applying knowledge from

one task to improve learning in another, reducing training time and
effort.

Training Data – The dataset used to teach an AI model by

exposing it to patterns and examples.

Unsupervised Learning – An ML approach that involves training

models on unlabeled data, allowing them to discover patterns
independently.

Validation Set – A dataset used to tune hyperparameters and

evaluate model performance before final deployment.

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