In this workshop, we will start by refactoring the linear regression we implemented in the previous lab so that it takes data from a tf. data.Dataset, and we will learn how to implement stochastic gradient descent with it. In this case, the original dataset will be synthetic and read by the tf.data API directly from memory.
In the second part, we will learn how to load a dataset with the tf.data API when the dataset resides on disk.
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