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 methods29
    • Biostatistics29
    • Descriptive statistics29
    • Gaussian processes29
    • Inferential statistics29
    • Markov processes29
    • Multivariate statistics29
    • Probabilistic graphical model29
    • Probability29
    • Statistics29
    • Statistics and probability29
    • Show N_FILTERS more
    • Tool
    • Galaxy28
    • scikit-learn16
    • GEMINI1
    • IWTomics1
    • PubMed1
    • Show N_FILTERS more
    • Content provider
    • GTN29
    • Show N_FILTERS more
    • Keyword
    • Statistics and machine learning
    • Galaxy Server administration66
    • Development in Galaxy45
    • Single Cell38
    • biodiversity36
    • microgalaxy33
    • Foundations of Data Science31
    • Ecology30
    • FAIR30
    • Transcriptomics29
    • jupyter-notebook29
    • training29
    • Microbiome28
    • Contributing to the Galaxy Training Material25
    • FAIR Data, Workflows, and Research25
    • FAIR principles22
    • data management22
    • Metadata21
    • Proteomics21
    • Genome Annotation20
    • ansible20
    • Assembly19
    • FAIR data19
    • Using Galaxy and Managing your Data18
    • git-gat18
    • Climate17
    • Data analysis16
    • Data management16
    • HemaFAIR16
    • Introduction to Galaxy Analyses16
    • Open Science16
    • Teaching and Hosting Galaxy training16
    • fair16
    • interactive-tools16
    • Research Data Management15
    • earth-system15
    • data stewardship14
    • Data management planning13
    • Epigenetics13
    • metagenomics13
    • work-in-progress13
    • Data reuse12
    • Data sharing12
    • Roslin Institute12
    • paper-replication12
    • prokaryote12
    • CONVERGE11
    • European research projects11
    • MIGHTS11
    • Ontologies11
    • Sequence analysis11
    • Variant Analysis11
    • Python10
    • Standards10
    • genes and genomes10
    • ocean10
    • plants10
    • research data management10
    • Bioinformatics9
    • DMP9
    • ELIXIR-CONVERGE9
    • cyoa9
    • transcriptomics9
    • Data management plan8
    • Evolution8
    • FAIR Data8
    • Galaxy Community Building8
    • Metabolomics8
    • assembly8
    • data visualisation8
    • español8
    • gmod8
    • label-free8
    • medicine and health8
    • nanopore8
    • Clinical data7
    • DDA7
    • EBV dataset7
    • EBV workflow7
    • Interoperability7
    • R7
    • Reproducibility7
    • SARS-CoV-27
    • Workflows7
    • dmp7
    • ecology7
    • jbrowse17
    • metabarcoding7
    • next generation sequencing7
    • programming7
    • reproducibility7
    • 16S6
    • Computational modelling6
    • Data Management6
    • Data Management Plan6
    • Data management planning6
    • EeLP6
    • Imaging6
    • Programming6
    • RStudio6
    • Show N_FILTERS more
    • Competency level
    • Beginner
    • Intermediate14
    • Show N_FILTERS more
    • Licence
    • Creative Commons Attribution 4.0 International29
    • Show N_FILTERS more
    • Target audience
    • Students29
    • Show N_FILTERS more
    • Author
    • Anup Kumar11
    • Kaivan Kamali8
    • Alireza Khanteymoori4
    • Amirhossein Naghsh Nilchi4
    • Björn Grüning4
    • Jeremy Goecks3
    • Junhao Qiu3
    • Paulo Cilas Morais Lyra Junior3
    • Daniel Blankenberg2
    • Khai Van Dang2
    • Simon Bray2
    • Bérénice Batut1
    • Dennis Lal group1
    • Ekaterina Polkh1
    • Fabio Cumbo1
    • Marie Gramm1
    • Marzia A Cremona1
    • Polina Polunina1
    • Vijay1
    • Show N_FILTERS more
    • Contributor
    • Saskia Hiltemann22
    • Björn Grüning19
    • Anup Kumar16
    • Helena Rasche16
    • Martin Čech14
    • Armin Dadras11
    • Kaivan Kamali8
    • Teresa Müller7
    • Alireza Khanteymoori5
    • Bérénice Batut5
    • Amirhossein Naghsh Nilchi4
    • Fabio Cumbo3
    • Paulo Cilas Morais Lyra Junior3
    • Cristóbal Gallardo2
    • Gildas Le Corguillé2
    • Michelle Terese Savage2
    • Simon Bray2
    • qiagu2
    • Bert Droesbeke1
    • Daniel Sobral1
    • Enis Afgan1
    • Junhao Qiu1
    • Mohammad Joudy1
    • Mélanie Petera1
    • Nate Coraor1
    • Niall Beard1
    • Nicola Soranzo1
    • Pavankumar Videm1
    • Vijay1
    • dlal-group1
    • Show N_FILTERS more
    • Resource type
    • e-learning20
    • slides9
    • Show N_FILTERS more
    • Related resource
    • Associated Training Datasets29
    • Associated Workflows27
    • 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

Keywords: Statistics and machine learning

and Competency level: Beginner

29 materials found
  • e-learning

    Clustering in Machine Learning

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

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

    • Beginner
    Statistics and probability Statistics and machine learning
  • slides

    Recurrent neural networks (RNN) Deep Learning - Part 2

    • 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
  • slides

    Image classification in Galaxy with fruit 360 dataset

    • Beginner
    Statistics and probability Statistics and machine learning
  • slides

    Convolutional neural networks (CNN) Deep Learning - Part 3

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

    Introduction to deep learning

    • Beginner
    Statistics and probability Statistics and machine learning
  • slides

    Feedforward neural networks (FNN) Deep Learning - Part 1

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