Classification with TensorFlow
In the last chapter, we covered linear regression with TensorFlow, where we looked at both simple and multiple linear regression; we also explored various metrics for evaluating regression models. We concluded the chapter with a real-world use case, where we built a salary prediction model, and we used this to predict the salaries of new employees based on a set of features. In this chapter, we will continue with modeling in TensorFlow – this time, by exploring classification problems with TensorFlow.
We will start by looking at the concept of classification modeling, after which we will examine the various evaluation metrics for classification modeling and how we can apply them to various use cases. We will look at binary, multi-class, and multi-label classification modeling. Finally, we will walk through a case study, putting all we have learned into practice by building a binary classification model to predict whether a student will drop...
