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Using Deep Learning to Solve Binary Classification Problems

In this chapter, we will use Keras and TensorFlow to solve a tricky binary classification problem. We will start by talking about the benefits and drawbacks of deep learning for this type of problem, and then we will go right into developing a solution using the same framework we established in Chapter 2, Using Deep Learning to Solve Regression Problems. Finally, we will cover Keras callbacks in greater depth and even use a custom callback to implement a per epoch receiver operating characteristic / area under the curve (ROC AUC) metric.

We will cover the following topics in this chapter:

  • Binary classification and deep neural networks
  • Case study – epileptic seizure recognition
  • Building a binary classifier in Keras
  • Using the checkpoint callback in Keras
  • Measuring ROC AUC in a custom callback
  • Measuring precision, recall, and f1-score
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