Introduction

An overview of the development process for machine learning models.

In this section you will be learning about the model execution process in TensorFlow. This involves model training, evaluation, and making predictions. The techniques and APIs introduced in the upcoming chapters are used by top industry professionals to easily create organized and efficient machine learning models.

The first model you create is going to be a classification model. Classification models take data observations and label them with a certain category. For example, classification models can used for tasks like fraud detection, where something is categorized as either fraud or legitimate.

The second model you create is going to be a regression model. Regression models take data observations and output a number. which which can be used for predicting sales with this course's supermarket dataset.

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