[held online] Summer School on Machine Learning and Big Data with Quantum Computing, 7-8 September 2020
Summer School on Machine Learning and Big Data with Quantum Computing (SMBQ 2020) Porto, Portugal, September 7-8, 2020 Web page: https://smbq2020.dcc.fc.up.pt/ ##################################### Machine Learning (ML) is an Artificial Intelligence (AI) branch, that focuses on developing algorithms to teach how computers learn from data to make decisions or predictions. Deep Learning (DL) is part of a broader family of ML algorithms, that is based on artificial neural networks. Arguably, DL techniques demand for big amounts of data and, as such, they require huge computational resources and advanced processing techniques. Cloud Computing is a well-known alternative to deal with big amounts of data, since its elasticity allows for an efficient scalability of huge computational resources, such as, data storage and processing power. On the other hand, Quantum Computing is an advanced processing technique, that uses the fundamentals of quantum mechanics to accelerate the process of solving highly complex problems. SMBQ 2020 addresses the current trends in AI and in the computational techniques that deal with big data demands, together with, a powerful processing technique that will shape the future of computation. During 2 days, from 7-8 September 2020, we will introduce concepts, discuss the current trends and provide direct practical experience in hands-on lessons. ##################################### Registration: Attendance is free, but it is required that participants register in advance by filling a form until 15 August, 2020. Prior to the event, information regarding the access of the live sessions will be sent to all registrants via email. https://smbq2020.dcc.fc.up.pt/#registration The number of participants is limited, thus the registration process closes once the limit is reached. For any further information, please send a message to SMBQ2020. ##################################### Contact Persons: Carlos Ferreira, Polytechnic Institute of Porto, LIAAD - INESC TEC, E-mail: cgf@isep.ipp.pt Miguel Areias, University of Porto, CRACS - INESC TEC, E-mail: miguel-areias@dcc.fc.up.pt Carlos Ferreira ISEP | Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto - PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail@isep.ipp.pt | www.isep.ipp.pt
participants (1)
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Carlos Ferreira