Mastering .NET Machine Learning

Summary

We covered a lot of ground in this chapter. We looked at k-means and PCA to help us find hidden relationships in our traffic datasets. We then built an application that took advantage of the insights we gleaned to make drivers more aware and, hopefully, safer. This application is unique because it blended both real-time machine learning modeling and human observations to provide the best possible outcome for the driver.

In the next chapter, we are going to look at some of the limitations of our coding so far in this book and see if we can improve on both model and feature selection.