Introduction to Hybrid Quantum-Classical Machine Learning
Quantum Computing. There is a lot of buzz about it, but it is still such a new field that many in the IT world have only a glancing familiarity with it, particularly when it is used for machine learning. How does quantum machine learning compare to standard or "classical" machine learning?
In this fast-paced webinar, Mission Data Scientist and Cybersecurity DSc. Dr. Alexander Perry will provide a brief but rigorous overview of hybrid quantum-classical machine learning (HQML). The focus will be on using noisy intermediate-scale quantum (NISQ) computers with classical computers. The perspective for this presentation will be an applied computing approach via The Heilmeier Catechism from DARPA (Defense Advanced Research Projects Agency).
The 60-minute webinar concludes with a moderated live question-and-answer period.
Capitol Technology University offers the webinar as a complimentary informational service. This webinar offers a Certificate of Attendance.
About the Presenter
Dr. Alexander Perry
Adjunct Professor
Dr. Alexander Perry is an adjunct professor at Capitol Technology University and a data scientist performing applied research in hybrid quantum-classical machine learning (HQML). His expertise includes Cyber, Data Science, Artificial Intelligence/Machine Learning (AI/ML), and Quantum Computing. During a career spanning nearly 30 years, his previous roles have included software engineer, system administrator, data scientist, technical director, and data science team lead. Dr. Perry completed his Doctor of Science (DSc) in Cybersecurity at Capitol Technology University.