Developing Kubeflow Pipelines: Kaggle’s Digit Recognizer Competition

Learn computer vision fundamentals with the famous MNIST data.

Oct 19, 2022 06:00 AM Pacific Time (US and Canada)

Kubeflow familiarity
Beginner to Intermediate

About the Workshop
In this workshop we’ll show how to turn Kaggle’s Digit Recognizer competition into a Kubeflow Pipeline using the KFP SDK and the Kale JupyterLab extension.

About the Kaggle Competition
MNIST (“Modified National Institute of Standards and Technology”) is the de facto “hello world” dataset of computer vision. Since its release in 1999, this classic dataset of handwritten images has served as the basis for benchmarking classification algorithms. As new machine learning techniques emerge, MNIST remains a reliable resource for researchers and learners alike. In this competition, your goal is to correctly identify digits from a dataset of tens of thousands of handwritten images.

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