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
    • Kernel methods
    • Python19
    • Python program19
    • Python script19
    • py19
    • Genome annotation14
    • Bayesian methods11
    • Biostatistics11
    • Descriptive statistics11
    • Exomes11
    • Gaussian processes11
    • Genomes11
    • Genomics11
    • Inferential statistics11
    • Markov processes11
    • Multivariate statistics11
    • Personal genomics11
    • Probabilistic graphical model11
    • Probability11
    • Statistics11
    • Statistics and probability11
    • Synthetic genomics11
    • Viral genomics11
    • Whole genomes11
    • Comparative transcriptomics10
    • R10
    • R program10
    • R script10
    • Transcriptome10
    • Transcriptomics10
    • Active learning9
    • Data rendering9
    • Data visualisation9
    • Ensembl learning9
    • Knowledge representation9
    • Machine learning9
    • MicroRNA sequencing9
    • Neural networks9
    • RNA sequencing9
    • RNA-Seq9
    • RNA-Seq analysis9
    • Recommender system9
    • Reinforcement learning9
    • Small RNA sequencing9
    • Small RNA-Seq9
    • Small-Seq9
    • Supervised learning9
    • Transcriptome profiling9
    • Unsupervised learning9
    • WTSS9
    • Whole transcriptome shotgun sequencing9
    • miRNA-seq9
    • Chromosome walking6
    • Clone verification6
    • Cloud computing6
    • Computer science6
    • DNA-Seq6
    • DNase-Seq6
    • HPC6
    • High performance computing6
    • High throughput sequencing6
    • High-performance computing6
    • High-throughput sequencing6
    • NGS6
    • NGS data analysis6
    • Next gen sequencing6
    • Next generation sequencing6
    • Panels6
    • Primer walking6
    • Sanger sequencing6
    • Sequencing6
    • Single-cell genomics6
    • Single-cell sequencing6
    • Targeted next-generation sequencing panels6
    • Bioinformatics5
    • Pipelines5
    • Software integration5
    • Tool integration5
    • Tool interoperability5
    • Variant pattern analysis5
    • Workflows5
    • Breakend assembly3
    • Data management3
    • Functional genome annotation3
    • Genome assembly3
    • Genomic assembly3
    • Metadata management3
    • Metagenome annotation3
    • Population genetics3
    • Research data management (RDM)3
    • Sequence assembly (genome assembly)3
    • Structural genome annotation3
    • DNA methylation2
    • Data privacy2
    • Data security2
    • Epigenetics2
    • FAIR data2
    • Findable, accessible, interoperable, reusable data2
    • Histone modification2
    • Metagenomics2
    • Show N_FILTERS more
    • Content provider
    • Glittr.org9
    • Show N_FILTERS more
    • Keyword
    • Machine learning9
    • R2
    • Artificial intelligence1
    • Data science1
    • General1
    • Protein structure1
    • Proteomics1
    • Python1
    • Show N_FILTERS more
    • Competency level
    • Not specified9
    • Show N_FILTERS more
    • Licence
    • MIT License
    • License Not Specified48
    • Creative Commons Attribution 4.0 International15
    • Creative Commons Attribution Share Alike 4.0 International6
    • Apache License 2.05
    • Creative Commons Attribution Non Commercial Share Alike 4.0 International3
    • Creative Commons Attribution Non Commercial No Derivatives 4.0 International1
    • GNU General Public License v3.0 only1
    • Show N_FILTERS more
    • Author
    • Gray Lab1
    • Instill AI1
    • Lex Fridman1
    • Paderborn University - LEA1
    • Phillip Lippe1
    • PickyBinders1
    • Ujjwal Karn1
    • girafe.ai1
    • mlr-org1
    • Show N_FILTERS more
    • Contributor
    • Adnan Siddiqui1
    • Alexander Timans1
    • AliAbdelwanis1
    • Andreas Bender1
    • Anton Petrov1
    • Avinash Sajjanshetty1
    • AweSIM1
    • Balaji Varatharajan1
    • Barnabas Haucke-Korber1
    • Bernd Bischl1
    • Bjarke Hautop1
    • Brandon Banks1
    • Britnie Carpentier1
    • Bryan Eikema1
    • Chenliang Xu1
    • Courtney Thomas1
    • Damir Pulatov1
    • Danial Syed1
    • Daniel Saggau1
    • Daniel Weber1
    • Danilo de Goede1
    • Darius Jakobeit1
    • Darío Hereñú1
    • David Knigge1
    • Dirk Eddelbuettel1
    • Florian1
    • Franz Srambical1
    • GabeAu791
    • Gabriele Cesa1
    • GalvinGao1
    • Girafe AI1
    • Giulio Starace1
    • Giuseppe Casalicchio1
    • Guz1
    • H-Chlor1
    • Hendrik Vater1
    • Ilze Amanda Auzina1
    • Imahn Shekhzadeh1
    • Jacob Hepkema1
    • Jakob Richter1
    • Jannes Muenchow1
    • Jay1
    • Jeffrey Gray1
    • Joe HUANG1
    • John Zobolas1
    • Julia Niebisch1
    • Lars Kotthoff1
    • Lennart Schneider1
    • Lex Fridman1
    • Li Ding1
    • Lona1
    • Lukas Burk1
    • M. Böcker1
    • Marc Becker1
    • Marvin Meyer1
    • Marvin N. Wright1
    • Maximilian Schenke1
    • Michael Chungyoun1
    • Michel Lang1
    • Miltiadis (Miltos) Kofinas1
    • Natalie Foss1
    • Nicholas G Reich1
    • Nuno Rocha1
    • Ochuko A.1
    • Oliver Wallscheid1
    • Patrick Schratz1
    • Peter Steinbach1
    • Phillip Lippe1
    • Phúc H. Lê Khắc1
    • Pietro Monticone1
    • Przemysław Biecek1
    • QiMing LIU1
    • Quinn H Koike1
    • Radoslav Neychev1
    • Raphael Sonabend-Friend1
    • Ray1
    • Samuele Papa1
    • Sebastian Fischer1
    • Sebastian G Gruber1
    • Shahab Einabadi1
    • Shitao Wu1
    • Sina Torfi1
    • Stefan Coors1
    • Susanne Dandl1
    • Toby Dylan Hocking1
    • Ujjwal Karn1
    • Valery Marchenkov1
    • Victor Tuekam1
    • Vladislav Goncharenko1
    • Wilhelm Kirchgässner1
    • alpz1
    • awinterstetter1
    • brian1
    • dymil1
    • ja-thomas1
    • kristosh1
    • mb7061
    • neychevr1
    • olivroy1
    • puv-sreev1
    • Show N_FILTERS more
    • Node
    • Switzerland9
    • Show N_FILTERS more
  • Only show materials from current space
  • Show disabled materials
  • Show materials with broken links
  • Show archived materials

Training materials

  • Subscribe via email

Email Subscription

Register training material

Scientific topics: Kernel methods

and Licence: MIT License

and Across all spaces: true

9 materials found
  • Graylab/DL4Proteins-notebooks

    ELIXIR node event
    Machine learning Protein structure Python Machine learning Artificial intelligence
  • mlr-org/mlr3book

    ELIXIR node event
    Machine learning Machine learning R
  • PickyBinders/geometric-learning-protein-structures-course

    ELIXIR node event
    Machine learning Proteomics Proteomics Machine learning
  • upb-lea/reinforcement_learning_course_materials

    ELIXIR node event
    Machine learning Machine learning
  • phlippe/uvadlc_notebooks

    ELIXIR node event
    Machine learning Machine learning
  • girafe-ai/ml-course

    ELIXIR node event
    Machine learning Machine learning
  • ujjwalkarn/DataScienceR

    ELIXIR node event
    Machine learning General R Machine learning
  • instillai/TensorFlow-Course

    ELIXIR node event
    Machine learning Machine learning
  • lexfridman/mit-deep-learning

    ELIXIR node event
    Machine learning Machine learning Data science
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.