Introduction to Hybrid Quantum-Classical Machine Learning
Join us on Thursday, May 23, 2024, Noon-1 p.m. Eastern
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 Ph.D. 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
Dr. Perry has an IT career spanning nearly 30 years. In 1995, he began as a mathematics summer hire at the U.S. Department of Defense (DoD). He moved into a contractor position in the DoD and, later, in other federal agencies, including the National Institutes of Health, on various tasks, including Unix network programming in C, packet-level protocol analysis, Natural Language Processing (NLP), and distributed computing. In 2013, Dr. Perry returned to government service at the Department of the Treasury, in the Office of Financial Research, as a Senior System Engineer focusing on data ingest automation and distributed computing. In 2014, Dr. Perry completed his Doctor of Science (D.Sc.) in cybersecurity at Capitol Technology University. The same year, he returned to the Department of Defence as a Software Engineer/System Administrator, Technical Director, data scientist, team lead, and section chief. Currently, Dr. Perry serves as a mission data scientist and performs advanced applied research in hybrid quantum-classical machine learning (HQML).