Building a regression model

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: Building a 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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