EVENTS

Dr. Behnam Yousefi, Institute of medical systems biology, UKE

This workshop is open to students, researchers, and clinicians keen to learn the essentials of machine learning and implementing it via Python. The aim of the course is to provide a comprehensive map of machine learning (and deep learning) methods with no specific background requirements. A little background in python can be helpful, though. We will focus on fundamentals of machine learning, validation methods, linear and nonlinear models, and feature reduction. The students will also get familiarized with the Python packages of Sci-kit Learn and Pytorch. The workshop will be in presence and therefore each participant should bring their own laptop (no ipads).

Topics
Types of machine learning: supervised and unsupervised
Validation  metrics and cross validation
Introduction to linear and nonlinear models include: Linear regression, Random forest, support vector machines, deep neural networks.
Feature reduction.
Regularization.