What differentiates deep learning from traditional machine learning?
Deep learning will do to software what the steam engine did to manufacturing.
How It Works:
Deep learning stacks multiple nonlinear layers (neurons) to automatically learn hierarchical feature representations unlike traditional ML, which relies on manual feature engineering.
Key Benefits:
- State-of-the-art accuracy: Excels on image, speech, and text tasks.
- Automatic features: Reduces manual data preprocessing.
- Scalability: Leverages GPUs/TPUs for large-scale training.
Real-World Use Cases:
- Speech recognition: Converting audio to text with high accuracy.
- Image segmentation: Medical imaging analysis.
FAQs
Do I need big compute?
What about overfitting?
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