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[MUSIC PLAYING] JOSH GORDON: Hey, everyone. Welcome back. Features are the way you represent your knowledge about the world for the classifier, and today Ill walk you through techniques you can use to represent your features and utilities TensorFlow provides to help. You use a dataset from the US census as an example, and the goal is to predict if someones income is greater than $50,000 based on attributes like their age and occupation. The dataset is stored as a CSV file, and previously weve seen how to use the column values directly as features. But today well use feature engineering to transform them into a more useful representation. As we go, Ill visualize what these transformations do using a tool called Facets, and you can find a link to it in the description. Youll also find complete code to train a TensorFlow estimator on this dataset. OK, lets get started. Lets begin with a numeric attribute like age, and think about how we can use it to predict income. Now if you th