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Achievements

Achievement: Pair Extraordinairex2Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault ContributorAchievement: Starstruck

Achievements

Achievement: Pair Extraordinairex2Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault ContributorAchievement: Starstruck

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Organizations

@tensorflow @keras-team

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  1. keras-hub Public

    Forked from keras-team/keras-hub

    Industry-strength Natural Language Processing workflows with Keras

    Python 3

  2. keras Public

    Forked from keras-team/keras

    Deep Learning for humans

    Python 2 1

  3. keras-cv Public

    Forked from keras-team/keras-cv

    Industry-strength Computer Vision workflows with Keras

    Python

  4. keras-io Public

    Forked from keras-team/keras-io

    Keras documentation, hosted live at keras.io

    Jupyter Notebook

778 contributions in the last year

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Activity overview

Contributed to keras-team/keras-hub, keras-team/keras, keras-team/keras-io and 6 other repositories
Loading A graph representing mattdangerw's contributions from March 24, 2024 to March 29, 2025. The contributions are 47% commits, 26% pull requests, 25% code review, 2% issues.

Contribution activity

March 2025

Created 5 commits in 3 repositories

Created a pull request in keras-team/keras that received 1 comment

Don't require jax on the numpy backend

We can still use it for the resize op, but we shouldn't fail to import without jax installed. Fixes #20966

+7 −1 lines changed • 1 comment
Opened 6 other pull requests in 3 repositories
Reviewed 26 pull requests in 3 repositories

Created an issue in keras-team/keras-hub that received 4 comments

Allow computer vision task models to run without tf.data

First step (of a few), to slowly relax our reliance on tf.data for preprocessing. Our text models are more heavily reliant on tf.data because of th…

4 comments
Opened 2 other issues in 2 repositories
10 contributions in private repositories Mar 6 – Mar 21
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