Training materials
Keywords: Machine learning
and Include disabled: true
and Scientific topics: Probabilistic graphical model
2 materials found
- Home
- Materials
Filter
Sort
-
-
Filter Clear filters
-
-
Scientific topic
- Probabilistic graphical model
- Active learning17
- Ensembl learning17
- Kernel methods17
- Knowledge representation17
- Machine learning17
- Neural networks17
- Recommender system17
- Reinforcement learning17
- Supervised learning17
- Unsupervised learning17
- Bayesian methods2
- Biostatistics2
- Descriptive statistics2
- Gaussian processes2
- Inferential statistics2
- Markov processes2
- Multivariate statistics2
- Probability2
- Statistics2
- Statistics and probability2
- Antimicrobial stewardship1
- Chromosome walking1
- Clone verification1
- DNA-Seq1
- DNase-Seq1
- Data rendering1
- Data visualisation1
- Exomes1
- Genome annotation1
- Genomes1
- Genomics1
- High throughput sequencing1
- High-throughput sequencing1
- Medical microbiology1
- Microbial genetics1
- Microbial physiology1
- Microbial surveillance1
- Microbiological surveillance1
- Microbiology1
- Molecular infection biology1
- Molecular microbiology1
- NGS1
- NGS data analysis1
- Network1
- Next gen sequencing1
- Next generation sequencing1
- Panels1
- Pathway1
- Pathway or network1
- Personal genomics1
- Pipelines1
- Primer walking1
- Sanger sequencing1
- Sequencing1
- Software integration1
- Synthetic genomics1
- Targeted next-generation sequencing panels1
- Tool integration1
- Tool interoperability1
- Viral genomics1
- Whole genomes1
- Workflows1
- Show N_FILTERS more
-
-
-
Content provider
- Elixir TeSS2
- Show N_FILTERS more
-
-
-
Difficulty level
- Not specified2
- Show N_FILTERS more
-
- Show materials from all spaces
- Hide disabled materials
- Show materials with broken links
- Show archived materials
