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Developing and integrating methods for fastai2 tabular with other datatypes

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fastai2_tabular_hybrid

Hybrid approaches to supporting more datatypes with fastai2 tabular

Contributers:

DataLoaders:

  • NumpyDataloader: uses NumPy as the backend to speed up performance up to ~8X fast.ai’s TabularPandas DataLoader.
  • TensorDataloader: uses PyTorch Tensor as the backend to speed up performance up to ~20X fast.ai’s TabularPandas DataLoader if entire Dataset can fit into GPU memory.

Contributers:

  • Zachary Mueller
  • Benjamin Warner

Directions for Contributing:

  1. Fork this repository into your GitHub Account
  2. Ensure that nbdev is installed on your system
  3. Make any changes and ensure that you run the following before commiting:
  • nbdev_build_lib
  • nbdev_clean_nbs
  1. Open a Pull Request with the library, and choose "From fork" to open one with the main repository.

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verified publisher icon muellerzr

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Developing and integrating methods for fastai2 tabular with other datatypes

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