EVENTS

Our events in the areas of Big Data and Research Innovation include a diverse set of topics such as Future, Strategy, Technology, Applications, and Management.

If you feel that your event or event series should be part of this event calendar, just contact us!

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Tuesday 28th - Thursday 30th May, 2024 | 09:00 - 12:00 a.m.

Machine Learning in Practice (intermediate level)

Seminar room 1.65, Center for Molecular Neurobiology Hamburg (ZMNH), Falkenried 94, 20251 HH

learn_bAIome offers workshops and trainings in biomedical AI/data science with tailored formats that take into account background, programming skills and intensity to provide unique, focused, and effective courses. These courses are free and open to students, clinicians, and researchers across academic institutions in Hamburg.

This workshop is open to students, researchers, and clinicians wanting to learn how machine learning is applied for biomedical datasets, the different classes of machine learning algorithms that may be used, as well as the best practices in selecting and evaluating algorithms, and their limitations.  The aim of the course is to provide concepts and tools to navigate the use of machine learning in the biomedical landscape. The course will use biological datasets and there will be hands-on components as well as discussions. Participants should already have taken an introduction to machine learning and be familiar with Python programming. The workshop will be in presence and therefore each participant should bring their own laptop (no ipads).

Topics

  • Taxonomy of machine learning algorithms
  • Linear regression, logistic regression and related methods
  • Decision trees
  • Support Vector Machines
  • Bias & Variance, curse of dimensionality
  • Representation learning
  • Neural networks and deep learning: MLPs, transformers, CNNs
  • Applications to RNAseq and imaging data

 

Universität Hamburg
Adeline Scharfenberg
Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein. 

Universität Hamburg
Adeline Scharfenberg
Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein. 

Universität Hamburg
Adeline Scharfenberg
Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein.