Machine Learning by Example

In the earlier chapters of this book we have seen how machine learning works and what the different machine learning techniques are. This chapter will explain how to apply these machine learning techniques to real-world problems: automatic classification (clustering) of an unknown dataset, dimensionality reduction of large datasets, recommendation models, anomaly detection, root cause analysis, engineering applications of supervised learning regression, predictive maintenance, image recognition, detection of different diseases, business process improvement, etc. Not only the specific applications will be explained but also tips and tricks and important sector-dependent machine learning recommendations. After reading this chapter you will be able to apply the machine learning techniques explained in the previous chapters to your own machine learning problems, even if they are different from the examples presented here.