awesome-experimental-standards-deep-learning
Repository collecting resources and best practices to improve experimental rigour in deep learning research.
https://github.com/kaleidophon/awesome-experimental-standards-deep-learning
Last synced: 4 days ago
JSON representation
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Experimental Standards for Deep Learning in Natural Language Processing Research
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Resources
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:bar_chart: Data
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:computer: Codebase & Model
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:microscope: Experiments & Analysis
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:page_facing_up: Publication
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Programming Languages
Categories
Sub Categories
Keywords
machine-learning
6
data-science
3
ai
2
data-version-control
2
developer-tools
2
reproducibility
2
unstructured-data
2
statistics
2
ml
1
machinelearning
1
hypothesis-tests
1
hypothesis-testing
1
dl
1
deeplearning
1
deep-neural-networks
1
deep-learning
1
compare-scores
1
metrics
1
neurips-2020
1
neurips
1
research-paper
1
publication
1
natural-language-processing
1
latex
1
bibtex
1
bibliography
1
ttest
1
statistical-tests
1
statistical-methods
1
pandas
1
multiple-comparisons
1
effect-size
1
correlations
1
cohens-d
1
circular-statistics
1
bayesian-statistics
1
anova
1
statistical-significance-test
1
statistical-significance
1
significance-testing
1
awesome-list
1