Walking through the NVidia AI Workbench's Kaggle competition kernel example project

The NVidia AI Workbench team has created a prototypical workspace for those wanting to participate in Kaggle competitions while running on their own hardware.  NVidia created a workbench project, NVidia Competition Kernel on GitHub, that integrates Kaggle's GPU container images along with Jupyter Notebooks that interface with Kaggle. The Kaggle images are the same ones they use in their data scientist environment. The project is configured to participate in the continuous, training, Digits competition where you train a model to recognize handwritten numerical digits. NVidia created the project in a way that can be used in other competitions of the same class.



 Three Notebooks

  1. Downloads the Training and Submission data
  2. Creates a model and trains the model using the training data. The notebook tunes the model against the training data. Then, it evaluates the Test data to generate what it thinks are the matches. The matches are written to a file.
  3. Uploads the CSV file containing its predictions against the test data.  Kaggle evaluates and scores that and displays it.

Video

See the video for more details.

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Created 2024 11



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