Discussion

Mark Hoogendoorn, Burkhardt Funk

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

Abstract

In this chapter, we list some of the important challenges we see in the field of machine learning for the quantified self.

LanguageEnglish
Title of host publicationMachine Learning for the Quantified Self
Subtitle of host publicationOn the Art of Learning from Sensory Data
PublisherSpringer/Verlag
Pages217-221
Number of pages5
ISBN (Electronic)9783319663081
ISBN (Print)9783319663074
DOIs
Publication statusPublished - 1 Jan 2018

Publication series

NameCognitive Systems Monographs
Volume35
ISSN (Print)1867-4925
ISSN (Electronic)1867-4933

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Learning systems

Cite this

Hoogendoorn, M., & Funk, B. (2018). Discussion. In Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data (pp. 217-221). (Cognitive Systems Monographs; Vol. 35). Springer/Verlag. https://doi.org/10.1007/978-3-319-66308-1_10
Hoogendoorn, Mark ; Funk, Burkhardt. / Discussion. Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data. Springer/Verlag, 2018. pp. 217-221 (Cognitive Systems Monographs).
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Hoogendoorn, M & Funk, B 2018, Discussion. in Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data. Cognitive Systems Monographs, vol. 35, Springer/Verlag, pp. 217-221. https://doi.org/10.1007/978-3-319-66308-1_10

Discussion. / Hoogendoorn, Mark; Funk, Burkhardt.

Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data. Springer/Verlag, 2018. p. 217-221 (Cognitive Systems Monographs; Vol. 35).

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

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Hoogendoorn M, Funk B. Discussion. In Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data. Springer/Verlag. 2018. p. 217-221. (Cognitive Systems Monographs). https://doi.org/10.1007/978-3-319-66308-1_10