COM 214 Lecture Notes - Lecture 4: Quantum Machine Learning, Machine Learning, Quantum System

• School: Barry University
• Department: Communication
• Course: COM 214
• Professor: William Sidies

Document Summary

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable. The theory serves as a bridge between biophysics and psychology. It is possible to predict learning curves from neurological variables and vice versa. Machine learning is an application of artificial intelligence (ai) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.