AutoML for the Win: A primer on letting machines do the work

Automated Machine Learning aims to reduce the human effort involved in machine learning and allow groups of all knowledge levels to benefit.

Jul 25, 2022, 4:00 – 5:00 PM

15
RSVP'd

RSVP Now

Key Themes

Machine Learning

About this event

Automated Machine Learning aims to reduce the human effort involved in machine learning and allow groups of all knowledge levels to benefit.🧠

In this talk, Dipti Sengupta gives a little background in Machine Learning and Automated Machine Learning (AutoML), the areas of AutoML, before taking a closer look at what is most in use today. We will build on the levels of knowledge, beginning with a no-code solution offered by Microsoft and peaking with a fully customizable library by the AutoML Lab in Freiburg.

Along the way, Dipti will share her experiences and opinions, and highlight practical advice on what not to do while creating better data models.👀

This event is intended to introduce the idea of Automated Machine Learning and be a starting point for leveraging Machine Learning, independent of technical background.💫

Speaker

  • Dipti Sengupta

    University of Freiburg

    MSc Student

Organizers

  • Sarper Melik Ertekin

    ETH Zurich

    GDSC Lead

  • Arthur Serres

    ETH Zürich

    GDSC Lead

  • Bahar Açılan

    ETH Zürich

    GDSC Lead

  • August Bøgh Rønberg

    Core Team Member

  • Simon Sure

    ETH Zürich

    Core Team Member

  • Annina Oswald

    ETH Zurich

    Core Team Member

  • Marcel Pokorski

    ETH Zurich

    Core Team Member

  • Nicola Stella

    Core Team Member

  • JB Conan

    Core Team Member

  • Elina Teplygina

    Core Team Member

  • Léon Noirclerc

    ETH

    Core Team Member

  • Anirudhh RAMESH

    Core Team Member

  • Anna Stawiska

    Core Team Member

  • Athena Schumacher

    Core Team Member

  • Hugo Fabrègues

    Core Team Member

  • Eric Nerger

    ETH Zürich

    Core Team Member

  • Gaukhar Yesmurzayeva

    Core Team Member

Contact Us