Deep Learning Study Circle Agenda and Course Structure

Slide Note
Embed
Share

Engage in a structured deep learning study circle led by Bo Bernhardsson, Kalle Ström, Magnus Fontes, Fredrik Bagge Carlsson, and Martin Karlsson. The course emphasizes hands-on experience, existing material usage, and active participation from all members. Explore various topics, projects, readings, and practical exercises in a collaborative learning environment.


Uploaded on Oct 02, 2024 | 0 Views


Download Presentation

Please find below an Image/Link to download the presentation.

The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author. Download presentation by click this link. If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.

E N D

Presentation Transcript


  1. Deep Learning - Study Circle Bo Bernhardsson, Kalle str m, Magnus Fontes, Fredrik Bagge Carlsson, Martin Karlsson

  2. Agenda Intro by me, Fontes FredrikB Kalle all Decide weekly meeting date Decide upon the first topics and responsible

  3. About the course Engineering perspective Hands on experience and intuition Use existing material

  4. Structure 1-2 persons responsible for a weekly meeting * Suggest reading material in good time * Also make some small exercise, (done in 0.5 day or so) use existing software and material from internet * Lead a 2 hour session around the topic

  5. To take the course for credits Lead at least one session Participate and solve at least half of the other sessions Make a small project, give a 10 min presentation Suggested: 7.5 hp

  6. Material Goodfellow Ch 6-20 + articles Datasets Platform, e.g. Tensorflow Competitions (e.g. Kaggle)

  7. Material https://github.com/ChristosChristofidis/aweso me-deep-learning

  8. BoBs todo list Google: Wavenet https://deepmind.com/blog/wavenet-generative-model-raw-audio/ https://codelabs.developers.google.com/codelabs/tensorflow-for- poets/#0 Bengio video DL: https://youtu.be/JuimBuvEWBg DeepLearning.tv youtube https://sites.google.com/site/brainrobotdata/home http://www.asimovinstitute.org/neural-network-zoo/ http://arxiv.org/abs/1609.02993

  9. Course Tools SLACK accept invitation Course home page Synapse email

  10. First Session week 1-2 Responsible: bob@control.lth.se + MartinK Register in Synapse and Slack Read Goodfellow part 2 (p167-487) Watch Bengio s vide lectures on DL (part1+2) https://youtu.be/JuimBuvEWBg Choose a DL platform and run a tutorial, present what you did (2 min)

  11. Participants Control: MartinK: SARAFUN, robotik, montering av mindre grejor, bilder, ljud, kraftsignaler etc Jacob: Coolt. Allm nt intresse. BoB: - -, BG, tidsserier Olof: Allm nt intresse Bagge: Robotar. Guided policy search Mattias: Allm nt intresse EIT: Lianhao Yin, lianhao.yin@energy.lth.se Joao Vieira <joao.vieira@eit.lth.se> Najmeh Abiri <Najmeh@thep.lu.se> Zhi Zhang <zhi.zhang@eit.lth.se> jonathan.sonnerup@eit.lth.se sha.hu@eit.lth.se jose.flordelis@eit.lth.se Math: kalle@maths.lth.se fontes@maths.lth.se ida.arvidsson@math.lth.se stefaningi@gmail.com johanb@maths.lth.se Maria Priisalu <maria.priisalu@math.lth.se> Others: Najmeh Abiri <Najmeh@thep.lu.se> Jacek Malec <jacek.malec@cs.lth.se> fredrik.dahlgren@ericsson.com robert.marklund@ericsson.com per.persson@ericsson.com boeliasson@yahoo.se

Related


More Related Content