2025-02-17 Introduction to Machine Learning with scikit-learn

Learn the basics of (classical) machine learning with scikit-learn

Reiter

Machine Learning with scikit-learn
You are familiar with Python and the scientific data stack (Numpy, Pandas etc.) but now want to learn how to model your data using Machine Learning? In this course you will discover scikit-learn, one of the most popular open-source packages for Machine Learning in Python.
Course Objectives:
  • scikit-learn principles: learn how to use scikit-learn functions in general as they all share common mechanisms
  • ML algorithms: learn about the diverse task that can be achieved with the library, including regression, classification, clustering etc.
  • Pre- and post-processing: learn how to make sure that your modelling makes sense using train/test sets, computing quality metrics such as precision, recall etc.
Target group
  • Students and Staff of UniBe.
Prerequisites
  • Participants must bring own laptops.
  • You should be familiar with Python and the scientific Python stack, in particular Numpy
Methods
Certificate
  • A certificate will be delivered to participants who have attended the whole training.
Coaches
  • Guillaume Witz is a Data scientist and software engineer in bio-imaging at University of Bern.
Time : 2025-02-17  09:00-17:00
Location : Room 220, Uni Mittelstrasse, Mittelstrasse 43
Online Participation:
Training language: English
Participants : Max 25
Registraion : Mandatory
Coaches : Guillaume Witz (lecturer and coach)
Prerequisites : Laptop
Certificate : Certificate for full training attendance
Repository
The Data Science Lab is there to boost your research by supporting you solving computing challenges. 
https://www.dsl.unibe.ch/