Imagine a toddler learning by observing the world. Machine learning uses data and artificial neural networks to recognize patterns in images, speech, and text. For example, pruning and knowledge distillation shrink models so voice assistants run smoothly on your phone without constant cloud access.
Key points
- Machine learning teaches systems to learn from data without explicit rules.
- Techniques like pruning, compression, and distillation optimize models for mobile and edge devices.
- Quantum ML combines qubits with algorithms to tackle complex problems at unprecedented speeds.
Q&A
- What is an Artificial Neural Network?
- How does knowledge distillation work?
- Why is pruning important in ML models?
- What potential does Quantum Machine Learning hold?
