Training eSupport System
  • Log In
    • Log in with LS Login
    • Login
    • Register
  • About
  • Events
  • Materials
  • e-Learning
  • Workflows
  • Collections
  • Learning paths
  • Directory
    • Providers
    • Nodes
    • Spaces

TeSS makes use of some necessary cookies to provide its core functionality. Additionally, we make use of Google Analytics to discover how people are using TeSS in order to help us improve the service. To opt out of this, choose the "Allow necessary cookies" option.

See our Privacy Policy for more information.

You can modify your cookie preferences at any time here, or from the link in the footer.

Allow necessary cookies Allow all cookies
  1. Home
  2. Materials

Filter

  • Sort

  • Filter Clear filters

    • Date added
    • In the last 24 hours
    • In the last 1 week
    • In the last 1 month
    • Scientific topic
    • Machine learning
    • Active learning2
    • Ensembl learning2
    • Kernel methods2
    • Knowledge representation2
    • Neural networks2
    • Recommender system2
    • Reinforcement learning2
    • Supervised learning2
    • Unsupervised learning2
    • Show N_FILTERS more
    • Competency level
    • Intermediate2
    • Show N_FILTERS more
    • Licence
    • License Not Specified2
    • Show N_FILTERS more
    • Target audience
    • PhD students2
    • Post Docs2
    • Show N_FILTERS more
    • Author
    • Morris Riedel
    • The Carpentries Incubator6
    • SIB Swiss Institute of Bioinformatics4
    • Emil Hvitfeldt2
    • Fred Hutch Data Science Lab2
    • Jasper Zuallaert2
    • Sven Degroeve2
    • fast.ai2
    • posit-conf-20232
    • posit::conf(2024)2
    • Alexander Botzki1
    • Alexander Botzki |1
    • Alexander Botzki | https://orcid.org/0000-0001-6691-42331
    • Anastassia Vorebieva1
    • Andra Waagmeester1
    • Andrei Sokolovskii1
    • Applied Machine Learning for Tabular Data1
    • BiotrAIn1
    • Bradley Boehmke1
    • Canadian Bioinformatics Workshops1
    • Computational Biology and Bioinformatics at UCLouvain1
    • David Dalpiaz1
    • Dr Euan McDonnell1
    • Dr Eva Caamano-Gutierrez1
    • Dr John Heap1
    • Dr Jordan Tzvetkov1
    • Fotis Psomopoulos1
    • Francesco Cremonesi1
    • Gray Lab1
    • Inria1
    • Instill AI1
    • Jose A Dianes1
    • Karel Berka1
    • Lex Fridman1
    • Liverpool Computational Biology Facility (CBF)1
    • Marian Novotny1
    • Matheus Lourenço1
    • Maxime Labonne1
    • Navid Nobani1
    • Neuromatch Academy1
    • Nicola Rennie1
    • Oscar Baruffa1
    • PAIR code1
    • Pablo Casas1
    • Paderborn University - LEA1
    • Philip Bowsher1
    • Phillip Lippe1
    • PickyBinders1
    • R Programming @ University of Cincinnati1
    • R. Burke Squires1
    • Raphael Mourad1
    • Salvatore Raieli1
    • Shawn Rhoads1
    • Thomas Guiziou1
    • Ujjwal Karn1
    • University of Liverpool1
    • VIB Training & Conferences1
    • Yury Kashnitsky1
    • bioinformatics.ca1
    • cambiotraining1
    • girafe.ai1
    • gladstone-institutes1
    • juexinwang1
    • mlr-org1
    • tidymodels1
    • udlbook1
    • Show N_FILTERS more
    • Resource type
    • Video2
    • Show N_FILTERS more
    • Node
    • Belgium2
    • Show N_FILTERS more
  • Show materials from all spaces
  • Show disabled materials
  • Show materials with broken links
  • Show archived materials

Training materials

  • Subscribe via email

Email Subscription

Register training material

Scientific topics: Machine learning

and Authors: Morris Riedel

2 materials found
  • Video

    Deep Learning using a Convolutional Neural Network

    ELIXIR node event
    •• Intermediate
    Machine learning
  • Video

    Introduction to Machine Learning Algorithms

    ELIXIR node event
    •• Intermediate
    Machine learning
Training eSupport System
[email protected]
Contribute
About TeSS
Browse Spaces
Funding & acknowledgements
Privacy
Cookie preferences
Version: 1.5.1
Source code
API documentation
Bioschemas testing tool

TeSS has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 676559.