Deep Learning
Deep learning is a branch of machine learning that uses neural networks with many stacked layers to learn patterns directly from data. The word deep refers to the number of layers. Each layer transforms the data a little further, letting the model learn complex features from raw images, text, audio, or sensor readings.
Instead of an engineer hand-writing the features a model should look for, a deep learning model learns them during training by adjusting millions of internal weights to reduce its errors on labeled or unlabeled examples. This usually requires large datasets and accelerated hardware such as GPUs.
In manufacturing, deep learning powers vision AI models that spot surface defects, missing components, or incorrect labels across product variations that would be hard to describe with fixed rules.
Deep learning is a subset of machine learning, which is itself a subset of artificial intelligence. Traditional machine learning methods, such as decision trees or linear regression, typically rely on features chosen by people, while deep learning learns its own features.