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10-days-of-grad

Neural Networks and Deep Learning

https://github.com/penkovsky/10-days-of-grad

Science Score: 26.0%

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    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
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    Academic publication links
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    Scientific vocabulary similarity
    Low similarity (2.6%) to scientific vocabulary

Keywords

convolutional-neural-networks deep-learning haskell neural-network
Last synced: 6 months ago · JSON representation

Repository

Neural Networks and Deep Learning

Basic Info
Statistics
  • Stars: 33
  • Watchers: 3
  • Forks: 7
  • Open Issues: 0
  • Releases: 0
Topics
convolutional-neural-networks deep-learning haskell neural-network
Created about 7 years ago · Last pushed about 2 years ago
Metadata Files
Readme Citation

README.md

10 Days Of Grad: Deep Learning From The First Principles

Neural networks in Haskell

  • Day 1: Neural network basics
  • Day 2: Multilayer neural networks
  • Day 3: Automatic differentiation
  • Day 4: Batch normalization and MNIST images
  • Day 5: Convolutional neural networks
  • Day 6: Binarized neural networks
  • Day 7: Deep Learning with Hasktorch
  • Day 8: Model Uncertainty Estimation
  • Day 9: Variational Autoencoders
  • Day 10: Deep Reinforcement Learning

Citation

BibTeX:

@misc{tendays, author = {Penkovsky, Bogdan}, title = {10 Days of Grad: Neural Networks and Deep Learning}, year = {2023}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/penkovsky/10-days-of-grad}} }

Owner

  • Login: penkovsky
  • Kind: user

GitHub Events

Total
  • Issues event: 2
  • Watch event: 3
  • Issue comment event: 2
  • Fork event: 1
Last Year
  • Issues event: 2
  • Watch event: 3
  • Issue comment event: 2
  • Fork event: 1

Issues and Pull Requests

Last synced: almost 2 years ago

All Time
  • Total issues: 2
  • Total pull requests: 1
  • Average time to close issues: almost 2 years
  • Average time to close pull requests: about 2 hours
  • Total issue authors: 2
  • Total pull request authors: 1
  • Average comments per issue: 10.5
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
Issue Authors
  • Pekarnya (1)
  • masterdezign (1)
  • jrp2014 (1)
Pull Request Authors
  • jrp2014 (1)
Top Labels
Issue Labels
Maintenance (1) enhancement (1)
Pull Request Labels

Dependencies

massiv/massiv-nn.cabal hackage
  • base >=4.7 && <4.13
  • bytestring *
  • massiv *
  • massiv-nn *
  • mwc-random *
  • random *
  • time *
day4/batchnorm.cabal hackage
  • MonadRandom *
  • array *
  • base >=4.7
  • batchnorm *
  • bytestring *
  • deepseq *
  • massiv *
  • massiv ==0.4.5.0
  • mnist-idx *
  • mwc-random *
  • random *
  • split *
  • streamly *
  • transformers *
  • vector *
day5/conv.cabal hackage
  • MonadRandom * benchmark
  • array * benchmark
  • backprop * benchmark
  • base >=4.7 && <4.13 benchmark
  • conv * benchmark
  • criterion * benchmark
  • deepseq * benchmark
  • massiv >=0.4.5.0 && <0.5 benchmark
  • microlens * benchmark
  • microlens-th * benchmark
  • mwc-random * benchmark
  • streamly * benchmark
  • MonadRandom *
  • array *
  • backprop *
  • base >=4.7 && <4.13
  • conv *
  • deepseq *
  • massiv >=0.4.5.0 && <0.5
  • massiv-io *
  • microlens *
  • microlens-th *
  • mnist-idx *
  • mwc-random *
  • one-liner *
  • one-liner-instances *
  • split *
  • streamly *
  • transformers *
  • vector *
day6/bnn.cabal hackage
  • MonadRandom *
  • array *
  • base >=4.7
  • bnn *
  • deepseq *
  • massiv >=0.4.5.0 && <0.5
  • massiv-io *
  • mnist-idx *
  • mwc-random *
  • split *
  • streamly *
  • transformers *
  • vector *
day10/project.cabal hackage
  • data-default-class >=0.1.2.0
  • libtorch-ffi *
  • pipes >=4.3.16
  • random *