Update regression.ipynb to explicitly cast one-hot encoding values #2316
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As currently written, the one-hot encoding step leaves the user with boolean dummy values that cause errors later in the tutorial as presently written, when passing the np.array() argument to Normalization.adapt(). The values need to be cast to a numerical type (e.g., int) either at the one-hot encoding step or the adapt() step.
PreviewPreview and run these notebook edits with Google Colab: Rendered notebook diffs available on ReviewNB.com.Format and styleUse the TensorFlow docs notebook tools to format for consistent source diffs and lint for style:$ python3 -m pip install -U --user git+https://github.com/tensorflow/docsIf commits are added to the pull request, synchronize your local branch: git pull origin patch-1
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Change the verbiage slightly to include reference to the Tensor docs and note the nature of the object needing uniform data types.
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As currently written, the one-hot encoding step leaves the user with boolean dummy values that cause errors later in the tutorial as presently written, when passing the np.array() argument to Normalization.adapt(). The values need to be cast to a numerical type (e.g., int) either at the one-hot encoding step or the adapt() step.