Deep Learning
Machine learning subfield using multi-layer neural networks to model complex concepts.
Machine learning subfield using multi-layer neural networks to model complex concepts.
Définition détaillée
Deep learning is a class of machine learning algorithms inspired by the human brain's structure. It uses artificial neural networks with many hidden layers (hence 'deep'). Each layer extracts increasingly abstract features: from pixels to shapes, to objects, to concepts. Main architectures include CNNs (images), RNNs/LSTMs (sequences), Transformers (text), and diffusion models (image generation). Deep learning drives recent AI advances.
Cas d'usage
Document fraud detection system: a deep neural network analyzes document patterns, metadata, and content to identify anomalies and fraud attempts in real-time.
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Questions fréquentes
What's the difference between deep learning and machine learning?
Machine learning encompasses all statistical learning techniques. Deep learning is a subset using deep neural networks, particularly effective for unstructured data (images, text, audio).
Does deep learning require a lot of data?
Generally yes, but transfer learning (reusing pre-trained models) achieves good results with just a few hundred examples.