This is a course on advanced deep learning taught as a 2nd year option at the engineering school T\u00e9l\u00e9com Physique Strasbourg<\/a>. It consists of 7*1,75 hours of lectures, and 6*2 hours of tutorials in pytorch.<\/p>\n Here are the lecture slides in pdf [NOTE: the slides will be updated along the progress of the course]<\/span>:<\/p>\n Here are the materials for the turorial \/ lab sessions:<\/p>\n These tutorials were originally created by Paul Magron<\/a>.<\/p>\n This is an introductory course to AI and machine learning, jointly delivered by Pierre Charbonnier, Hassen Dira and myself to the whole 2nd year class of the engineering school T\u00e9l\u00e9com Physique Strasbourg<\/a>, between September and December 2025. It consists of 7*1,75 hours of lectures and 7,5 hours of tutorials in scikit-learn. The slides for my lectures are below.<\/p>\n Chapter 1 & 2: Introduction to AI and Machine Learning<\/strong><\/p>\n Chapter 5: Deep Learning<\/strong><\/p>\n Chapter 6: Machine Learning in Practice<\/strong><\/p>\n This is the material for the lecture and tutorial I gave at the 2025 Autumn School Series in Acoustics (ASSA 2025) in Eindhoven, on the topic \u00ab\u00a0Machine Learning for Acoustics\u00a0\u00bb (website<\/a>), which took place on November 3-7, 2025.<\/p>\n This is the material for the lectures and tutorial I gave at the 2025 summer school on Deep Learning & Applications at the university of Strasbourg (website<\/a>), which took place on August 25-29, 2025.<\/p>\n On December 9th 2021, I gave a virtual lecture entitled \u00ab\u00a0Machine Learning for Indoor Acoustics\u00a0\u00bb<\/strong> at the Intelligent Sensing Winter School<\/a> of the Queen Mary University of London. This year’s themes were \u00ab\u00a0AI for sound perception, AI for visual perception, AI for multimodal perception\u00a0\u00bb. You can download the slides here: QMUL_CIS_Winter_School_deleforge_09.12.2021_split.pdf<\/a>.<\/p>\n On September 13th 2019, I gave a lecture entitled \u00ab\u00a0Taking the Best of Physics and Machine Learning in Robot Audition\u00a0\u00bb<\/a> at the IEEE S3P 2019 Summer School<\/a> in Arenzano, Italy. This year’s theme was \u00ab\u00a0Signal Processing for Autonomous Systems\u00a0\u00bb. You can download the slides here: S3P2019_deleforge_animated.pdf<\/a>.<\/p>\n This a short course taught at the university of Rennes in 2017 and 2018, consisting of 2*2 hours of lectures and 2 hours of tutorial. Here are the slides (In English) of my lectures on Auditory Scene Synthesis and Analysis (Spatialization, Localization, Separation)<\/strong> :\u00a0cours_ISTIC_casa_2017_english.pdf<\/a><\/p>\n On August the 24th 2015,\u00a0Mikkel Schmidt<\/a> and I were invited to give a tutorial on\u00a0Bayesian Learning for Signal Processing<\/strong> at LVA\/ICA 2015’s summer school<\/strong> in Liberec (Czech Republic). Here are the slides of the two parts I presented<\/p>\n This is a series of four 3-hour long practical sessions in Matlab on unsupervised learning taught at the Engineering school T\u00e9l\u00e9com Physique Strasbourg<\/a> (2021 – 2024).<\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" Advanced Deep Learning at T\u00e9l\u00e9com Physique Strasbourg (2026) This is a course on advanced deep learning taught as a 2nd year option at the engineering school T\u00e9l\u00e9com Physique Strasbourg. It consists of 7*1,75 hours of lectures, and 6*2 hours of tutorials in pytorch. Here are the lecture slides in pdf [NOTE: the slides will be […]<\/p>\n","protected":false},"author":176,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-239","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/members.loria.fr\/ADeleforge\/wp-json\/wp\/v2\/pages\/239","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/members.loria.fr\/ADeleforge\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/members.loria.fr\/ADeleforge\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/members.loria.fr\/ADeleforge\/wp-json\/wp\/v2\/users\/176"}],"replies":[{"embeddable":true,"href":"https:\/\/members.loria.fr\/ADeleforge\/wp-json\/wp\/v2\/comments?post=239"}],"version-history":[{"count":53,"href":"https:\/\/members.loria.fr\/ADeleforge\/wp-json\/wp\/v2\/pages\/239\/revisions"}],"predecessor-version":[{"id":721,"href":"https:\/\/members.loria.fr\/ADeleforge\/wp-json\/wp\/v2\/pages\/239\/revisions\/721"}],"wp:attachment":[{"href":"https:\/\/members.loria.fr\/ADeleforge\/wp-json\/wp\/v2\/media?parent=239"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n
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Machine Learning & A.I. at T\u00e9l\u00e9com Physique Strasbourg (2025)<\/h1>\n
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Autumn School Series in Acoustics (ASSA 2025) in Eindhoven – \u00ab\u00a0Machine Learning for Acoustics\u00a0\u00bb<\/h1>\n
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Summer School 2025 in Strasbourg – \u00ab\u00a0Deep Learning & Applications\u00a0\u00bb<\/h1>\n
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Intelligent Sensing Winter School 2021<\/h1>\n
IEEE S3P 2019 Summer School in Arenzano<\/h1>\n
Master ISTIC – Module VAI<\/h1>\n
Bayesian Learning for Signal Processing<\/h1>\n
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\nbayesian_multichannel_and_conclusion_electronic.pdf<\/a><\/li>\n<\/ul>\nUnsupervised Learning<\/h1>\n
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