In this chapter, we tried to complement our existing machine learning skills by discussing best practices in model selection and hyperparameter tuning. You learned how to tweak the hyperparameters of a model using grid search and cross-validation in both OpenCV and scikit-learn. We also talked about a wide variety of evaluation metrics and how to chain algorithms into a pipeline. Now, you are almost ready to start working on some real-world problems on your own.
In the next chapter, you will be introduced to an exciting and a new topic, that is, OpenVINO toolkit, which was one of the key releases in OpenCV 4.0.
