Deep Learning
A subset of machine learning involving neural networks with multiple layers, enabling the modeling of complex patterns in data.
Definition
Uses multi-layer (deep) neural architectures—convolutional, recurrent, transformer—to automatically learn hierarchical feature representations from raw input (images, text, audio). Deep-learning pipelines demand large labeled datasets, specialized hardware (GPUs/TPUs), explainability tools, and robust monitoring for drift and adversarial vulnerabilities.
Real-World Example
A medical-imaging startup trains a deep CNN on 100,000 labeled X-rays to detect pneumonia. They use GPUs for training, apply explainability heat maps to highlight diseased regions, and continuously monitor model accuracy in production, retraining when new scanner types arrive.
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