Teaching Deep Learning, a boisterous ever-evolving field

Alfredo Canziani
Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:30-34, 2022.

Abstract

Machine and deep learning techniques are actively being developed with over 150 papers submitted daily to arXiv, each of which is introducing its own notation. To offer a course that reflects the latest developments of the field and illustrate them in a cohesive and consistent manner, one needs to systematically consume the literature, summarise and standardise it, implement working examples, and deliver a concise and consistent presentation of a given topic. This paper reports all the best practices developed by the author in their last decade of teaching experience.

Cite this Paper

BibTeX
@InProceedings{pmlr-v170-canziani22a, title = {Teaching Deep Learning, a boisterous ever-evolving field}, author = {Canziani, Alfredo}, booktitle = {Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop}, pages = {30--34}, year = {2022}, editor = {Kinnaird, Katherine M. and Steinbach, Peter and Guhr, Oliver}, volume = {170}, series = {Proceedings of Machine Learning Research}, month = {08--13 Sep}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v170/canziani22a/canziani22a.pdf}, url = {https://proceedings.mlr.press/v170/canziani22a.html}, abstract = {Machine and deep learning techniques are actively being developed with over 150 papers submitted daily to arXiv, each of which is introducing its own notation. To offer a course that reflects the latest developments of the field and illustrate them in a cohesive and consistent manner, one needs to systematically consume the literature, summarise and standardise it, implement working examples, and deliver a concise and consistent presentation of a given topic. This paper reports all the best practices developed by the author in their last decade of teaching experience.} }
Endnote
%0 Conference Paper %T Teaching Deep Learning, a boisterous ever-evolving field %A Alfredo Canziani %B Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop %C Proceedings of Machine Learning Research %D 2022 %E Katherine M. Kinnaird %E Peter Steinbach %E Oliver Guhr %F pmlr-v170-canziani22a %I PMLR %P 30--34 %U https://proceedings.mlr.press/v170/canziani22a.html %V 170 %X Machine and deep learning techniques are actively being developed with over 150 papers submitted daily to arXiv, each of which is introducing its own notation. To offer a course that reflects the latest developments of the field and illustrate them in a cohesive and consistent manner, one needs to systematically consume the literature, summarise and standardise it, implement working examples, and deliver a concise and consistent presentation of a given topic. This paper reports all the best practices developed by the author in their last decade of teaching experience.
APA
Canziani, A.. (2022). Teaching Deep Learning, a boisterous ever-evolving field. Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, in Proceedings of Machine Learning Research 170:30-34 Available from https://proceedings.mlr.press/v170/canziani22a.html.

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