Since we've explored placeholders and variables, let's build an example model for regression analysis, similar to the one we created in Chapter 13, *Parallelizing Neural Network Training with TensorFlow*, where our goal is to implement a linear regression model: .

In this model, *w* and *b* are the two parameters of this simple regression model that need to be defined as variables. Note that *x* is the input to the model, which we can define as a placeholder. Furthermore, recall that for training this model, we need to formulate a cost function. Here, we use the **Mean Squared Error** (**MSE**) cost function that we defined in Chapter ...

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