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Table Of Contents
IoT Edge Computing with MicroK8s
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In this section, we will be using the Fashion MNIST dataset and TensorFlow’s Basic classification to build the pipeline step by step and turn the example ML model into a Kubeflow pipeline.
Before deploying Kubeflow, we will look at the dataset that we are going to use. Fashion-MNIST (https://github.com/zalandoresearch/fashion-mnist) is a Zalando article image dataset that includes a training set of 60,000 samples and a test set of 10,000 examples. Each sample is a 28 x 28 grayscale image with a label from one of 10 categories.
Each training or test item in the dataset is assigned to one of the following labels:
Table 9.1 – Categories in the Fashion MNIST dataset
Now that our dataset is ready, we can launch a new notebook server via the Kubeflow dashboard.
You can start...