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
    • Bayesian methods34
    • Biostatistics34
    • Descriptive statistics34
    • Gaussian processes34
    • Inferential statistics34
    • Markov processes34
    • Multivariate statistics34
    • Probabilistic graphical model34
    • Probability34
    • Statistics34
    • Statistics and probability34
    • Show N_FILTERS more
    • Tool
    • Galaxy24
    • scikit-learn11
    • GEMINI1
    • IWTomics1
    • PubMed1
    • Show N_FILTERS more
    • Content provider
    • GTN34
    • Show N_FILTERS more
    • Keyword
    • Statistics and machine learning
    • jupyter-notebook54
    • Foundations of Data Science48
    • biodiversity46
    • microgalaxy41
    • Galaxy Server administration40
    • Proteomics35
    • Single Cell34
    • Ecology30
    • Microbiome27
    • Genome Annotation24
    • Transcriptomics24
    • Contributing to the Galaxy Training Material23
    • FAIR Data, Workflows, and Research23
    • Using Galaxy and Managing your Data23
    • Rare Diseases & Research20
    • ansible20
    • Imaging19
    • git-gat18
    • interactive-tools18
    • Assembly17
    • Data management17
    • Variant Analysis17
    • work-in-progress17
    • Development in Galaxy16
    • fair16
    • jbrowse116
    • Teaching and Hosting Galaxy training15
    • elixir15
    • gmod15
    • earth-system14
    • Climate13
    • Introduction to Galaxy Analyses13
    • FAIR12
    • Introduction12
    • paper-replication12
    • prokaryote12
    • MIGHTS11
    • cyoa11
    • Image segmentation10
    • Sequence analysis10
    • assembly10
    • data stewardship10
    • eukaryote10
    • plants10
    • CONVERGE9
    • DDA9
    • Metabolomics9
    • R9
    • ai-ml9
    • covid199
    • label-free9
    • metagenomics9
    • ocean9
    • one-health9
    • Computational chemistry8
    • Epigenetics8
    • Galaxy Community Building8
    • PDBe8
    • workflows8
    • 10x7
    • EBV dataset7
    • EBV workflow7
    • Metadata7
    • Protein families7
    • collections7
    • data management7
    • dmp7
    • español7
    • metabarcoding7
    • nanopore7
    • transcriptomics7
    • Genome sequencing6
    • Overlay6
    • SARS-CoV-26
    • Sequence alignments6
    • Variants6
    • deutsch6
    • ecology6
    • illumina6
    • italiano6
    • rmarkdown-notebook6
    • train-the-trainers6
    • virology6
    • 16S5
    • Bioimaging5
    • Large Language Model5
    • Network analysis5
    • Programmatic access5
    • SQL5
    • Small molecules5
    • Systems biology5
    • deploying5
    • jobs5
    • label-TMT115
    • mouse5
    • ro-crate5
    • Community4
    • Conversion4
    • DIA4
    • Show N_FILTERS more
    • Competency level
    • Beginner20
    • Intermediate14
    • Show N_FILTERS more
    • Licence
    • Creative Commons Attribution 4.0 International34
    • Show N_FILTERS more
    • Target audience
    • Students34
    • Show N_FILTERS more
    • Author
    • Anup Kumar9
    • Bérénice Batut6
    • Raphael Mourad5
    • Alireza Khanteymoori4
    • Amirhossein Naghsh Nilchi4
    • Björn Grüning4
    • Kaivan Kamali4
    • Jeremy Goecks3
    • Junhao Qiu3
    • Paulo Cilas Morais Lyra Junior3
    • Alyssa Pybus2
    • Daniel Blankenberg2
    • Fabio Cumbo2
    • Fotis E. Psomopoulos2
    • Khai Van Dang2
    • Ralf Gabriels2
    • Simon Bray2
    • Dennis Lal group1
    • Ekaterina Polkh1
    • Marie Gramm1
    • Marzia A Cremona1
    • Polina Polunina1
    • Stella Fragkouli1
    • Vijay1
    • Wandrille Duchemin1
    • Show N_FILTERS more
    • Contributor
    • Saskia Hiltemann25
    • Björn Grüning24
    • Anup Kumar23
    • Helena Rasche15
    • Bérénice Batut14
    • Martin Čech12
    • Armin Dadras9
    • Teresa Müller6
    • Alireza Khanteymoori5
    • Kaivan Kamali5
    • Wandrille Duchemin5
    • olisand5
    • Amirhossein Naghsh Nilchi4
    • Fabio Cumbo4
    • Paulo Cilas Morais Lyra Junior3
    • Delphine Lariviere2
    • Gildas Le Corguillé2
    • Michelle Terese Savage2
    • Nate Coraor2
    • qiagu2
    • Anthony Bretaudeau1
    • Bert Droesbeke1
    • Daniel Blankenberg1
    • Daniel Sobral1
    • Enis Afgan1
    • Junhao Qiu1
    • Mohammad Joudy1
    • Mélanie Petera1
    • Niall Beard1
    • Nicola Soranzo1
    • Pavankumar Videm1
    • Simon Bray1
    • Stella Fragkouli1
    • Vijay1
    • dlal-group1
    • Show N_FILTERS more
    • Resource type
    • e-learning
    • slides9
    • Show N_FILTERS more
    • Related resource
    • Associated Training Datasets24
    • Associated Workflows22
    • Jupyter Notebook (with Solutions)9
    • Jupyter Notebook (without Solutions)9
    • Show N_FILTERS more
  • Show materials from all spaces
  • Show disabled materials
  • Show materials with broken links
  • Show archived materials

e-Learning

  • Subscribe via email

Email Subscription

Register training material

Resource type: e-learning

and Keywords: Statistics and machine learning

34 e-learning materials found
  • e-learning

    Deep Learning (Part 2) - Recurrent neural networks (RNN)

    • Beginner
    Statistics and probability Statistics and machine learning
  • e-learning

    Deep Learning (Part 3) - Convolutional neural networks (CNN)

    • Beginner
    Statistics and probability Statistics and machine learning
  • e-learning

    Deep Learning (Part 1) - Feedforward neural networks (FNN)

    • Beginner
    Statistics and probability Statistics and machine learning
  • e-learning

    Introduction to deep learning

    • Beginner
    Statistics and probability Statistics and machine learning
  • 1
  • 2
  • 3
  • 4
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.