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VERSION:2.0
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DTSTAMP:20260705T095300Z
UID:98455cae-ce22-4ccb-8830-22bbfd55d777
DTSTART:20201217T090000Z
DTEND:20201218T000000Z
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. However\, deep learning models are far from straightforward 
 to implement correctly due to the many different hyperparameter settings\,
  optimization procedures\, architecture choices\, etc. In this course\, we
  will make use of Jupyter Notebook and Keras\, which are both based on Pyt
 hon\, to apply deep learning techniques on both bio informatics and bio im
 age informatics data. We aim to work towards applications that participant
 s would like to study.
SUMMARY:Deep learning in biology
URL;VALUE=URI:https://training.vib.be/product/263
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