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 methods
    • R19
    • R program19
    • R script19
    • Python15
    • Python program15
    • Python script15
    • py15
    • Active learning13
    • Biostatistics13
    • Descriptive statistics13
    • Ensembl learning13
    • Gaussian processes13
    • Inferential statistics13
    • Kernel methods13
    • Knowledge representation13
    • Machine learning13
    • Markov processes13
    • Multivariate statistics13
    • Neural networks13
    • Probabilistic graphical model13
    • Probability13
    • Recommender system13
    • Reinforcement learning13
    • Statistics13
    • Statistics and probability13
    • Supervised learning13
    • Unsupervised learning13
    • Data rendering5
    • Data visualisation5
    • Data management2
    • Metadata management2
    • MicroRNA sequencing2
    • RNA sequencing2
    • RNA-Seq2
    • RNA-Seq analysis2
    • Research data management (RDM)2
    • Single-cell genomics2
    • Single-cell sequencing2
    • Small RNA sequencing2
    • Small RNA-Seq2
    • Small-Seq2
    • Transcriptome profiling2
    • WTSS2
    • Whole transcriptome shotgun sequencing2
    • miRNA-seq2
    • Exomes1
    • Genome annotation1
    • Genomes1
    • Genomics1
    • Metagenomics1
    • Personal genomics1
    • Pipelines1
    • R markdown1
    • Shotgun metagenomics1
    • Software integration1
    • Synthetic genomics1
    • Tool integration1
    • Tool interoperability1
    • Viral genomics1
    • Whole genomes1
    • Workflows1
    • Show N_FILTERS more
    • Content provider
    • Glittr.org12
    • ERGA Knowledge Hub1
    • Show N_FILTERS more
    • Keyword
    • Data science
    • Statistics74
    • Statistics and machine learning43
    • R41
    • Machine learning16
    • Python9
    • ai-ml9
    • elixir9
    • jupyter-notebook8
    • Data visualization6
    • RNA-seq6
    • Genomics5
    • Large Language Model5
    • General4
    • Single-cell sequencing4
    • Transcriptomics4
    • interactive-tools4
    • Next generation sequencing3
    • Version control3
    • work-in-progress3
    • Biostatistics2
    • Pathways and Networks2
    • Reproducibility2
    • Unix/Linux2
    • Variant analysis2
    • deep-learning2
    • jupyter-lab2
    • machine-learning2
    • statistics2
    • ATAC-seq1
    • Artificial intelligence1
    • Automated testing1
    • Data management1
    • Deep Learning1
    • Digital Humanities1
    • EeLP1
    • GLEAM1
    • HAM10000 Dataset1
    • HANCOCK Dataset1
    • Health Services1
    • Image Classification1
    • Image Learner1
    • LORIS Score Model1
    • Machine Learning1
    • Multimodal Learning1
    • Multiomics1
    • Open Access1
    • Open Science1
    • Open Source Software1
    • Open access1
    • Open source code1
    • Pan-cancer1
    • Phylogenetics / Phylogenomics1
    • Python for Data Analysis1
    • Quarto1
    • R Programming1
    • RAP1
    • Recurrence Prediction1
    • Reproducible Analytical Pipeline1
    • Reproducible Environment1
    • Reproducible Research1
    • Reproducible Science1
    • Rmarkdown1
    • SimPy1
    • Simulation1
    • Skin Lesion Classification1
    • Spatial transcriptomics1
    • Statistical tests1
    • Tabular Learner1
    • Workflows1
    • biostatistics1
    • cancer biomarkers1
    • dephosphorylation-site-prediction1
    • discrete-event simulation1
    • eLearning1
    • fine-tuning1
    • image-segmentation1
    • machine learning1
    • microbial ecosystems1
    • microbiome1
    • oncogenes and tumor suppressor genes1
    • protein-3D-structure1
    • reproduce1
    • reproducible research1
    • simmer1
    • text mining1
    • Show N_FILTERS more
    • Competency level
    • Not specified13
    • Show N_FILTERS more
    • Licence
    • License Not Specified9
    • Creative Commons Attribution Share Alike 4.0 International2
    • Apache License 2.01
    • MIT License1
    • Show N_FILTERS more
    • Author
    • Emil Hvitfeldt1
    • Michael Pyrcz1
    • ModernDive1
    • OpenIntro1
    • Oscar Baruffa1
    • PAIR code1
    • Pablo Casas1
    • Reusable and Reproducible Healthcare Simulations in Python and R1
    • SIB Swiss Institute of Bioinformatics1
    • Stephanie Hicks1
    • Stephen Turner1
    • Surgical Informatics1
    • Show N_FILTERS more
    • Contributor
    • Emil Hvitfeldt2
    • Metehan GÜNGÖR2
    • e-linc2
    • Adam Fleischhacker1
    • Adam Pearce1
    • Adejumo Ridwan Suleiman1
    • Alan T. Arnholt1
    • Albert Y. Kim1
    • Allison Theobold1
    • Amy Heather1
    • Ana B1
    • Andrew Bray1
    • Andrew Heiss1
    • Andy Coenen1
    • Antoine Bichat1
    • Becki R1
    • Ben Baumer1
    • Bjørn Peare Bartholdy1
    • Bryan Shalloway1
    • Carlos Paniagua1
    • Chip Oglesby1
    • Christophe Dervieux1
    • Clayton Hughes1
    • Colin Fay1
    • Colin Rundel1
    • Damien Ready1
    • David Solito1
    • Debbie Yuster1
    • Dorothy Bishop1
    • Dr. Chester Ismay1
    • Dr. Saurav Singla1
    • Eric Leung1
    • Erik Erhardt1
    • Erin LaBrecque1
    • Ezekiel Adebayo Ogundepo1
    • GaryBikini1
    • Guy Incognito1
    • Isabella Velásquez1
    • Jacob Bien1
    • Jamie Lendrum1
    • Jannik Buhr1
    • Javier Orraca-Deatcu1
    • Jean-Marie Pivette1
    • Jo Hardin1
    • Joel Ostblom1
    • John Coene1
    • Jon Calder1
    • Julia Silge1
    • Kelly N. Bodwin1
    • Kenny Armstrong1
    • Kristian Lundby Gjerde1
    • Kyle Willett1
    • Legana Fingerhut1
    • Little Miss Data1
    • Lluís Revilla1
    • Louis Aslett1
    • Marium Tapal1
    • Matt Roumaya1
    • Maëlle Salmon1
    • Michael Dorman1
    • Michael Pyrcz1
    • Mine Cetinkaya-Rundel1
    • Mitsuo Shiota1
    • Mohit Sharma1
    • Murad Khalil1
    • Måns Thulin1
    • Natalie Nelson1
    • Nick Paterno1
    • Nicole Radziwill1
    • Nistara Randhawa1
    • Ondrej Pekacek1
    • OpenIntro1
    • Oscar Baruffa1
    • Pablo Casas1
    • Pablo Seibelt1
    • Peter Baumgartner1
    • Pietro Monticone1
    • Piklu Mallick1
    • Przemysław Biecek1
    • Rachel Marcone1
    • Rafael A Irizarry1
    • Rami Krispin1
    • Riinu Pius1
    • Roberto Rosati1
    • Robin Donatello1
    • Roseline2241
    • Roy Keyes1
    • Russell Rayner1
    • RutendoM1
    • Shamsudddeen Hassan Muhammad1
    • Shitao Wu1
    • Sol Feuerwerker1
    • Stacey Hancock1
    • Stanley E. Lazic1
    • Starry Zhou1
    • Stephanie Hicks1
    • Stephen Turner1
    • Stéphane Guillou1
    • Thomas Mailund1
    • Tobias Rockel1
    • Show N_FILTERS more
    • Node
    • Switzerland13
    • 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: Bayesian methods

and Keywords: Data science

13 materials found
  • SurgicalInformatics/healthyr_book

    ELIXIR node event
    Statistics and probability R Data science Statistics
  • oscarbaruffa/BigBookofR

    ELIXIR node event
    Data visualisation Workflows Machine learning Statistics and probability R Data science Data visualization Machine learning Statistics Version control …
  • moderndive/ModernDive_book

    ELIXIR node event
    Statistics and probability R Statistics Data science
  • 1
  • 2
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.