19405701
Lecture
SoSe 22: Machine Learning in Bioinformatics
Philipp Florian Benner, Hugues Richard
Comments
The goal of this course is to introduce all major concepts of machine learning (classification and regression) with tutorials applying those concepts to typical problems in bioinformatics. We will introduce several machine learning models and highlight the assumptions behind techniques and their limitations in terms of model complexity, run-time, memory consumption. After this lecture, students will be able to select appropriate machine learning methods for solving typical problems in bioinformatics. They will gain sufficient knowledge to also implement and extend these methods on their own.
Contents:
-Benchmarking of machine learning models
-Naive Bayes
-Clustering and mixture models
-Hidden Markov Models
-Regression and Partial Least Squares
-Kernel Regression
-Support Vector Machines
-Neural Networks
-Regularization and Feature Selection
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12 Class schedule
Regular appointments
Mon, 2022-04-25 08:00 - 10:00
Machine Learning in Bioinformatics
Mon, 2022-05-02 08:00 - 10:00
Machine Learning in Bioinformatics
Mon, 2022-05-09 08:00 - 10:00
Machine Learning in Bioinformatics
Mon, 2022-05-16 08:00 - 10:00
Machine Learning in Bioinformatics
Mon, 2022-05-23 08:00 - 10:00
Machine Learning in Bioinformatics
Mon, 2022-05-30 08:00 - 10:00
Machine Learning in Bioinformatics
Mon, 2022-06-13 08:00 - 10:00
Machine Learning in Bioinformatics
Mon, 2022-06-20 08:00 - 10:00
Machine Learning in Bioinformatics
Mon, 2022-06-27 08:00 - 10:00
Machine Learning in Bioinformatics
Mon, 2022-07-04 08:00 - 10:00
Machine Learning in Bioinformatics
Mon, 2022-07-11 08:00 - 10:00
Machine Learning in Bioinformatics
Mon, 2022-07-18 08:00 - 10:00
Machine Learning in Bioinformatics