Summary
In this chapter, we discussed classification modeling and looked at the main types of classification problems. We also discussed the main types of metrics for the evaluation of classification models and how to best apply them to real-world use cases. Then, we looked at a real-world use case, where we learned how to build, compile, and train a classification model with TensorFlow for a binary classification problem.
Finally, we learned, hands-on, how to evaluate our classification models. We have now completed the first section of this book. Get ready for the next sections, where we will see the power of TensorFlow in its full glory as we work on unstructured data (image and text data).