Classical Ml

Quantum Machine Learning, Explained: Superposition, Entanglement, and Why the Field Is Still Mostly Theory

Quantum machine learning (QML) offers a fundamentally different approach to data processing by leveraging quantum phenomena like superposition and entanglement in exponentially large mathematical spaces. While theoretically promising exponential speed-ups for specific problems, QML remains largely theoretical due to current hardware limitations and the challenge of identifying genuine, provable quantum advantages.