https://github.com/compomics/intro-to-deep-learning

Practical introduction to neural networks with Pytorch and Lightning

https://github.com/compomics/intro-to-deep-learning

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (0.4%) to scientific vocabulary

Keywords

convolutional-neural-networks lightning neural-networks pytorch recurrent-neural-networks tutorial
Last synced: 5 months ago · JSON representation

Repository

Practical introduction to neural networks with Pytorch and Lightning

Basic Info
  • Host: GitHub
  • Owner: CompOmics
  • License: cc-by-4.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 662 KB
Statistics
  • Stars: 1
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
convolutional-neural-networks lightning neural-networks pytorch recurrent-neural-networks tutorial
Created 10 months ago · Last pushed 9 months ago
Metadata Files
Readme License

README.md

intro-to-deep-learning

Owner

  • Name: Computational Omics and Systems Biology Group
  • Login: CompOmics
  • Kind: organization
  • Email: compomics.list@gmail.com

The CompOmics group, headed by Prof. Dr. Lennart Martens, specializes in the management, analysis and integration of high-throughput Omics data.

GitHub Events

Total
  • Watch event: 1
  • Push event: 3
  • Public event: 1
Last Year
  • Watch event: 1
  • Push event: 3
  • Public event: 1

Dependencies

requirements.txt pypi
  • lightning >=2.5,<3
  • matplotlib >=3.10,<4
  • numpy >=2.2,<3
  • pandas >=2.2,<3
  • pillow >=11.2,<12
  • pytorch-lightning >=2.5,<3
  • scikit-learn >=1.6,<2
  • scipy >=1.15,<2
  • seaborn >=0.13,<1
  • torch >=2,<3
  • torchvision >=0.22,<1
  • tqdm >=4.67,<5
  • wandb >=0.19,<1