Please note: This instance is for testing/development, and any content submitted may be changed or deleted without warning.
Training eSupport System
  • Log In
    • Login
    • Register
  • About
  • Events
  • Materials
  • e-Learning
  • Workflows
  • Collections
  • Learning paths
  • Directory
    • Trainers
    • Providers
    • Nodes

TeSS makes use of some necessary cookies to provide its core functionality.

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
  1. Home
  2. Materials

Filter

  • Sort

  • Filter Clear filters

    • Scientific topic
    • Bayesian methods
    • Algorithms7
    • Computer programming7
    • Data structures7
    • Programming languages7
    • Software development7
    • Software engineering7
    • Epigenomics5
    • Comparative transcriptomics4
    • Transcriptome4
    • Transcriptomics4
    • Assembly2
    • Biological sequences2
    • Biostatistics2
    • Community analysis2
    • Descriptive statistics2
    • Environmental microbiology2
    • Exomes2
    • Exometabolomics2
    • Gaussian processes2
    • Genome annotation2
    • Genomes2
    • Genomics2
    • Inferential statistics2
    • LC-MS-based metabolomics2
    • MS-based metabolomics2
    • MS-based targeted metabolomics2
    • MS-based untargeted metabolomics2
    • Markov processes2
    • Mass spectrometry-based metabolomics2
    • Metabolites2
    • Metabolome2
    • Metabolomics2
    • Metabonomics2
    • Metagenomics2
    • Microbial ecology2
    • Microbiome2
    • Molecular community analysis2
    • Multivariate statistics2
    • NMR-based metabolomics2
    • Personal genomics2
    • Probabilistic graphical model2
    • Probability2
    • Sequence analysis2
    • Sequence assembly2
    • Sequence databases2
    • Shotgun metagenomics2
    • Statistics2
    • Statistics and probability2
    • Synthetic genomics2
    • Viral genomics2
    • Whole genomes2
    • Bottom-up proteomics1
    • DNA variation1
    • Diffraction experiment1
    • Discovery proteomics1
    • Genetic variation1
    • Genomic variation1
    • Imaging1
    • MS-based targeted proteomics1
    • MS-based untargeted proteomics1
    • Metaproteomics1
    • Microscopy1
    • Microscopy imaging1
    • Mutation1
    • Optical super resolution microscopy1
    • Peptide identification1
    • Photonic force microscopy1
    • Photonic microscopy1
    • Polymorphism1
    • Protein and peptide identification1
    • Proteomics1
    • Quantitative proteomics1
    • Somatic mutations1
    • Targeted proteomics1
    • Top-down proteomics1
    • Show N_FILTERS more
    • Tool
    • Galaxy2
    • scikit-learn2
    • Show N_FILTERS more
    • Content provider
    • Galaxy Training2
    • Show N_FILTERS more
    • Keyword
    • Statistics and machine learning2
    • Show N_FILTERS more
    • Difficulty level
    • Beginner2
    • Show N_FILTERS more
    • Licence
    • Creative Commons Attribution 4.0 International2
    • Show N_FILTERS more
    • Target audience
    • Students2
    • Show N_FILTERS more
    • Author
    • Kaivan Kamali2
    • Show N_FILTERS more
    • Contributor
    • Cristóbal Gallardo
    • Saskia Hiltemann4
    • Björn Grüning3
    • Martin Čech3
    • Armin Dadras2
    • Helena Rasche2
    • Kaivan Kamali2
    • Teresa Müller2
    • Anup Kumar1
    • Bérénice Batut1
    • Simon Bray1
    • Show N_FILTERS more
    • Resource type
    • slides
    • Show N_FILTERS more
    • Related resource
    • Associated Training Datasets2
    • Associated Workflows2
    • Show N_FILTERS more
  • Show disabled materials
  • Show archived materials
    • Date added
    • In the last 24 hours
    • In the last 1 week
    • In the last 1 month

Training materials

  • Subscribe via email

Email Subscription

Register training material

Scientific topics: Bayesian methods

and Contributors: Cristóbal Gallardo

and Resource type: slides

2 materials found
  • slides

    Feedforward neural networks (FNN) Deep Learning - Part 1

    • 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
Training eSupport System
contact@example.com
Contribute
About TeSS
Funding & acknowledgements
Privacy
Cookie preferences
Version: 1.5.0
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.