Quantum Machine Learning with Covalent
Offered By: Advanced Cyberinfrastructure Training at RPI via YouTube
Course Description
Overview
Explore quantum machine learning concepts and applications using Covalent in this comprehensive lecture presented by Dr. Anna Hughes. Delve into the intersection of quantum computing and machine learning, gaining insights into how Covalent facilitates the development and implementation of quantum algorithms for machine learning tasks. Learn about the potential advantages of quantum approaches in solving complex computational problems and discover practical techniques for leveraging quantum resources in machine learning workflows. Gain a deeper understanding of the current state and future prospects of quantum machine learning, equipping yourself with valuable knowledge to navigate this cutting-edge field.
Syllabus
Quantum Machine Learning with Covalent
Taught by
Advanced Cyberinfrastructure Training at RPI
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent