Definition
Deep Learning is a subset of machine learning that uses multi-layered neural networks to progressively extract higher-level features from raw input.
Why "Deep"? The term refers to the number of layers in the network. Deep networks have many hidden layers (sometimes hundreds), allowing them to learn hierarchical representations.
- **Key Architectures:**
- CNNs: Convolutional Neural Networks for images
- RNNs: Recurrent Neural Networks for sequences
- Transformers: Attention-based networks for NLP
Requirements: - Large amounts of training data - Significant computational power (GPUs/TPUs) - Careful architecture design
Examples
Face recognition, autonomous vehicles, language translation.
Related Terms
A subset of AI where systems learn and improve from experience without being explicitly programmed.
Computing systems inspired by biological neural networks in the human brain.
A neural network architecture using self-attention mechanisms, the foundation of modern LLMs.
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