Deep learning is a type of machine learning that uses neural networks with many layers to learn complex patterns. It excels with large amounts of unstructured data such as images, audio and text.
Fine-tuning is further training of an existing model on a smaller, task-specific dataset so it adopts a particular style, format or skill. It changes how a model behaves without the cost of training a new one from scratch.
Machine learning is a branch of AI in which systems learn patterns from data to make predictions or decisions. The behaviour comes from training on examples rather than from rules written by hand.
A transformer is a neural network architecture that uses attention to weigh the relationships between all parts of an input. It is the basis of most modern language models.
Computer vision is the field of AI that lets software interpret images and video. Typical tasks are classifying objects, detecting defects, reading text and tracking movement.
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