Quantum Computing and Machine Learning

Topic repeated at 2 different times, please join the session that is best suited for your time zone.
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.

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Please join us at the session that is best suited to your time zone. Note that this topic is:
1. Repeated at two different times to accommodate various time zones, because it is
2. Posted simultaneously in multiple meetup groups world-wide
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It is recommended that you register at this Webex link ahead of time to receive a calendar invite and reminder. https://ibm.webex.com/weblink/register/r75ffeec48a2cce2401f554a02572fb07