TY - GEN
T1 - Visualization for Machine Learning
AU - Xenopoulos, Peter
AU - Nonato, Luis Gustavo
AU - Silva, Claudio
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - As machine learning has increased in popularity, visualization has taken an important role in analyzing and communicating aspects of machine learning models. Increasingly, visualization techniques are being used across a broad set of domains and in business-critical use cases. Oftentimes, these visualizations convey non-trivial machine learning concepts, utilize complex visual representations, or demand user interaction. In this tutorial, we seek to provide a foundational understanding, to a broad audience, of the ways in which we can use visualization for machine learning tasks. In particular, we detail visual techniques for model assessment, model understanding, and dimensionality reduction. Furthermore, we outline foundations and recent work in emerging visualization topics such as topological data analysis and understanding deep learning model internals.
AB - As machine learning has increased in popularity, visualization has taken an important role in analyzing and communicating aspects of machine learning models. Increasingly, visualization techniques are being used across a broad set of domains and in business-critical use cases. Oftentimes, these visualizations convey non-trivial machine learning concepts, utilize complex visual representations, or demand user interaction. In this tutorial, we seek to provide a foundational understanding, to a broad audience, of the ways in which we can use visualization for machine learning tasks. In particular, we detail visual techniques for model assessment, model understanding, and dimensionality reduction. Furthermore, we outline foundations and recent work in emerging visualization topics such as topological data analysis and understanding deep learning model internals.
KW - machine learning
KW - visualization
UR - http://www.scopus.com/inward/record.url?scp=85146421569&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146421569&partnerID=8YFLogxK
U2 - 10.1109/SIBGRAPI55357.2022.9991759
DO - 10.1109/SIBGRAPI55357.2022.9991759
M3 - Conference contribution
AN - SCOPUS:85146421569
T3 - Proceedings - 2022 35th Conference on Graphics, Patterns, and Images, SIBGRAPI 2022
SP - 294
EP - 301
BT - Proceedings - 2022 35th Conference on Graphics, Patterns, and Images, SIBGRAPI 2022
A2 - de Carvalho, Bruno Motta
A2 - Goncalves, Luiz Marcos Garcia
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th Conference on Graphics, Patterns, and Images, SIBGRAPI 2022
Y2 - 24 October 2022 through 27 October 2022
ER -