Quantum computing is poised to potentially have an impact on machine learning methods. In this seminar, we will cover the current state and future prospects of machine learning with quantum computers. This includes algorithms and models such as quantum kernel estimation, variational quantum classifiers, quantum neural networks, and quantum generative-adversarial networks (QGANs). We will also demonstrate the capabilities of the Qiskit Machine Learning open source software project.
Note that this is part 4 of an 8-session series on Quantum Computing on Mar 22/23, Apr 5/6, Apr 19/20, May 3/4, May 17/18, May 31/Jun 1, Jun 14/15, Jul 5/6. The sessions are not prerequisites for each other, and are not recorded. We will provide reference links and do quick recaps of previous content as required, so if you miss an earlier session, you can still get value from subsequent sessions.
Presenter: Eric Michiels
Eric Michiels is an Executive Architect at IBM, meaning he transforms business requirements of his customers into IT based solutions, including new innovative technologies. Eric is a Master of Science in Mathematics and Informatics. Eric is also an IBM Quantum Technical Ambassador and Qiskit Advocate and in this role he assists customers and academics to get started with their Quantum Journey.
You might also want to check out the other events hosted through this Meetup Group at: https://www.meetup.com/technical-group-hosted-by-ibm/