In this section, you will learn about using the Keras wrapper with scikit-learn, a very helpful tool that allows us to use Keras models as part of a scikit-learn workflow. As a result, scikit-learn methods and functions, such as the one for performing cross-validation, can be easily applied to Keras models. You will learn, step-by-step, how to implement what you learned about cross-validation in the previous section using scikit-learn. Furthermore, you will learn to use cross-validation in order to evaluate Keras deep learning models using the Keras wrapper with scikit-learn. Lastly, you will practice what you learned on a problem involving a real dataset.
When it comes to general machine learning and data analysis, the scikit-learn library is much richer and easier to use than Keras. That is why being able to use scikit-learn methods on Keras models will be of great value.
Fortunately, Keras comes with a helpful wrapper...
