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  1. Setting up a Jupyterhub Dockercontainer to spawn Jupyter Notebooks with GPU support (containing Tensorflow, Pytorch and Keras)

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  2. Repository for Kubach et al. bioRxiv/2019/804682 (2019)

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  3. Jupyter Notebook with Tensorflow, Pytorch and Keras with GPU support

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  4. This library helps with the key pre- and postprocessing steps necessary to use whole-slide images in deep-learning/ai projects.

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  6. Forked from surmenok/keras_lr_finder

    Plots the change of the loss function of a Keras model when the learning rate is exponentially increasing.

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Repositories

  • wsi_processing_pipeline

    This library helps with the key pre- and postprocessing steps necessary to use whole-slide images in deep-learning/ai projects.

    Jupyter Notebook 2 0 0 0 Updated Sep 16, 2021
  • FCDIIb_TSC

    Repository for Kubach et al. bioRxiv/2019/804682 (2019)

    Python 5 0 0 2 Updated Sep 8, 2021
  • Methylr2py

    Python wrapped R packages for methylation array analysis

    Jupyter Notebook 0 0 0 0 Updated Aug 23, 2021
  • GPU-Jupyterhub

    Setting up a Jupyterhub Dockercontainer to spawn Jupyter Notebooks with GPU support (containing Tensorflow, Pytorch and Keras)

    CSS 23 7 0 0 Updated Aug 21, 2019
  • keras_lr_finder

    Plots the change of the loss function of a Keras model when the learning rate is exponentially increasing.

    Python 0 MIT 59 0 0 Updated Jul 22, 2019
  • GPU-Jupyter-Notebook

    Jupyter Notebook with Tensorflow, Pytorch and Keras with GPU support

    Dockerfile 2 1 0 0 Updated Dec 8, 2018
  • nvidia-docker-gpu

    Setting up GPU support with docker-compose, nvidia-docker on Ubuntu 16.04 LTS

    1 1 0 0 Updated Feb 20, 2018

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