Machine Learning/Quantum Machine Learning

Introduction to Quantum Computing

Quantum Machine Learning

• Feature Map

This self-study, online course provides a general framework for working with and thinking about Quantum Machine Learning (QML).

This online tutorial contains about eight (8) hours of content and is targeted at individuals who  are comfortable with undergraduate-level mathematics and quantum computing fundamentals.

This online tutorial contains the key concepts in quantum machine learning:

• parameterized quantum circuits,
• training these circuits, and
• applying these circuits to basic problems. 

The learning objectives for the course include:

• understand the state of the field,
• be familiar with recent developments in both supervised and unsupervised learning
  • such as quantum kernels and
  • general adversarial networks.