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DTSTAMP:20260704T061837Z
UID:bafa47d0-bff0-4556-8cd1-ba68e68f835b
DTSTART:20211122T090000Z
DTEND:20211123T000000Z
DESCRIPTION:Large amounts of data and compute resources have enabled the de
 velopment of high-performance machine learning models. This is particularl
 y due to deep learning techniques. By looking at many data samples\, these
  models can find structure in the data that is useful for predictive and e
 xplorative analysis: e.g. classification\, clustering\, data generation\, 
 dimensionality reduction\, etc. The most popular applications within biote
 chnology are concerned with image segmentation\, diagnostics\, sequence an
 alysis\, etc.\n\nHowever\, deep learning models are far from straightforwa
 rd to implement correctly due to the many different hyperparameter setting
 s\, optimization procedures\, architecture choices\, etc.\n\nIn this cours
 e\, we will make use of Jupyter Notebook and PyTorch\, which are both base
 d on Python\, to apply deep learning techniques on both bio informatics an
 d bio image informatics data. We aim to work towards applications that par
 ticipants would like to study.
SUMMARY:Deep learning in biology
URL;VALUE=URI:https://training.vib.be/product/354
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