ODSC West 2020: Introduction to Generative Modeling Using Quantum Machine Learning
This course is available only as a part of subscription plans.
Overview
Ever wondered how quantum computers work, and how they do machine learning? With quantum computing technologies nearing the ear of commercialization and quantum advantage, machine learning has been proposed as one of the most promising applications. One of the areas in which quantum computing is showing great potential is in generative models in unsupervised and semi-supervised learning.
In this training you will develop a basic understanding of quantum computing and how it can be used in machine learning models, with special emphasis on generative models. We will focus on a particular architecture, the quantum circuit Born machine (QCBM), and use it to generate a simple dataset of bars and stripes.
No previous knowledge of quantum computing and generative model is needed for this workshop.
Training Overview
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ODSC West 2020: Introduction to Generative Modeling Using Quantum Machine Learning
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Training Overview and Author Bio
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Before you get started: Prerequisites and Resources
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Introduction to Generative Modeling Using Quantum Machine Learning
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Instructor Bio:
Quantum AI Research Scientist | Author of Grokking Machine Learning | Zapata Computing
Luis Serrano
Luis Serrano is a Quantum AI Research Scientist at Zapata Computing. He is the author of the book Grokking Machine Learning and maintains a popular YouTube channel where he explains machine learning in pedestrian terms.
Luis has previously worked in machine learning at Apple and Google, and at Udacity as the head of content for AI and data science. He has a PhD in mathematics from the University of Michigan, a masters and bachelors from the University of Waterloo, and worked as a postdoctoral researcher in mathematics at the University of Quebec at Montreal.
Quantum Applications Intern | Zapata Computing
Kaitlin Gili
Kaitlin Gili is a Quantum Applications Intern at Zapata Computing. She has previously worked at Los Alamos National Laboratory and the IBMQ hub within Keio University as a quantum algorithm intern, and at the University of Oxford as a visiting quantum hardware research student. Kaitlin is passionate about quantum computing outreach for young scientists and has previously delivered quantum computing workshops to Girls Who Code middle/high school programs. She received her Bachelors in Physics from Stevens Institute of Technology and will be starting her PhD in Physics at the University of Oxford in January 2021.
Senior Quantum Scientist | Zapata Computing
Alejandro Perdomo, PhD
Alejandro Perdomo-Ortiz is a Lead Quantum Application Scientist at Zapata Computing. He did his graduate studies, M.A and Ph.D. in Chemical Physics, at Harvard University. For over 12 years, he has worked to enhance the performance of quantum computing algorithms with physics-based approaches while maintaining a practical, application-relevant perspective. Before joining Zapata Computing, Alejandro spent over 5 years at NASA’s Quantum Artificial Intelligence Laboratory (NASA QuAIL), where he was the quantum machine learning technical lead. Between NASA and joining Zapata, he co-founded a consulting company called Qubitera LLC, which was acquired by Rigetti.