Prospects and Challenges for Quantum Machine Learning - Class 3
Offered By: ICTP-SAIFR via YouTube
Course Description
Overview
Explore the prospects and challenges of quantum machine learning in this comprehensive lecture by Marco Cerezo from Los Alamos National Laboratory, USA. Delve into the cutting-edge intersection of quantum computing and machine learning, examining potential applications and obstacles in the field. Gain insights into the latest research and developments as Cerezo discusses how quantum technologies could revolutionize artificial intelligence and data analysis. Understand the current limitations and future possibilities of quantum machine learning, and discover how it may impact various industries and scientific disciplines. This third class in the series provides an in-depth look at the evolving landscape of quantum computing and its implications for machine learning algorithms and techniques.
Syllabus
Marco Cerezo: Prospects and Challenges for Quantum Machine Learning - Class 3
Taught by
ICTP-SAIFR
Related Courses
Automata TheoryStanford University via edX Introduction to Computational Thinking and Data Science
Massachusetts Institute of Technology via edX 算法设计与分析 Design and Analysis of Algorithms
Peking University via Coursera How to Win Coding Competitions: Secrets of Champions
ITMO University via edX Introdução à Ciência da Computação com Python Parte 2
Universidade de São Paulo via Coursera