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Usable Machine Learning - Catastrophic CupCakes

Features

The initial repository was for the 'Usable ML' software project course at FU Berlin, provided by Fraunhofer AISEC. Students will develop a graphical user interface that allows creating machine learning models and manipulating them. Possible features include:

Training Interface

  • start training
  • interrupt training
  • continue training
  • adjust parameters (e.g., learning rate, loss function, momentum, dropout-rate) (0.5 P)
    • before the training
    • during the training
  • revert to an earlier epoch (1 P)
  • freeze parts of the model (1 P)

Training Monitor

  • display accuracy and loss over time for training set
  • indicate point in training where a parameter was changed
  • display accuracy and loss over time for test set (0.5 P)
  • display layer-specific information (e.g., gradients) (1 - 2 P)
  • compare different runs (1 P)
  • fork graph when parameters of earlier epochs are changed (1.5 P)

Model Creator

  • create models using a GUI (2 P)
  • change the composition of layers (1 P)
  • change aspects of the layers (e.g., sizes) (0.5 P)

Model Evaluator

  • select stored model to be evaluated (0.5 P)
  • evaluate per-class accuracy on test set (or training set, or arbitrary dataset) (1 P)
  • display special examples which (2 P)
    • are falsely predicted
    • are predicted with a small loss

Items in bold are expected as a minimum feature set.

Items in cursiv are implemented.

Extra Features

  • Machine Learning/CNN Explanations
  • Interactive Visualization of Convolution
  • Interactive Tutorial
  • Input Drawn Number (with Heatmap & Softmax Results)
  • Model Leaderboard
  • Highlighting and sorting of highest classification

Installation

Python3.10 or newer is required

venv

  1. create venv enviroment

    python -m venv venv

  2. Install PyTorch into your environment.

Follow official instructions or just install via pip when enviroment is active

  1. Install additional requirements
      . venv/bin/activate
      pip install -r requirements
  1. Activate/Deactivate enviroment
      . venv/bin/activate
      . venv/bin/deactivate

Usage

  1. Activate enviroment (see above)

  2. Run the app

python app.py

License

This project is licensed under the GNU Affero General Public License v3.0.