Introduction to Machine Learning in Python

Date: 09th-10th April 2024, Time: 9:00-12:00 each day

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

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

Language: English

Description: 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).


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.