The Lisbon Machine Learning Summer School (LxMLS)
The Lisbon Machine Learning Summer School (LxMLS) will be a 6-day in-person event, covering a range of machine learning (ML) topics, from theory to practice, that are important in solving natural language processing problems arising in different application areas. It is intended for researchers and graduate students, in the fields of Natural Language Processing (NLP) and computational linguistics, computer scientists interested in statistics and machine learning, and industry practitioners who desire a more in depth understanding of these subjects. Although previous deep knowledge of NLP and ML is not required, some background on mathematics and programming is expected from the students.
The organisation is composed by Instituto Superior Técnico (IST), the Instituto de Telecomunicações, the Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa (INESC-ID), the Lisbon ELLIS Unit for Learning and Intelligent Systems (LUMLIS), Unbabel, Zendesk, and IBM Research.
Date: July 19-25
Location: Congress Center of Instituto Superior Técnico
Application deadline: April 28
Know more here
About INESC-ID
INESC-ID, “Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento em Lisboa” is a Research and Development and Innovation Organization (R&D+i) in the fields of Computer Science and Electrical and Computer Engineering. INESC-ID mission is to produce added value to people and society, supporting the response of public policies to scientific, health, environmental, cultural, social, economic and political challenges. INESC-ID promotes cooperation between academia and industry by addressing research on daily life issues, such as healthcare, space, mobility, agri-food, industry 4.0, and smart grids. This high level of knowledge transfer is achieved through both competitive research projects and direct contracted research. Public and private entities have therefore access to a pool of knowledge, resources and services provided through the unique competencies available at the institution.
INESC-ID is supported by:
