April 2017
Intermediate to advanced
406 pages
10h 15m
English
Anomaly detection is a very common problem that can be found in many applications.
At the start of this chapter, we described a few possible use cases and highlighted the major types and differences according to the context and application requirements.
We briefly covered some of the popular techniques for solving anomaly detection using shallow machine learning algorithms. The major differences can be found in the way features are generated. In shallow machine learning, this is generally a manual task, also called feature engineering. The advantage of using deep learning is that it can automatically learn smart data representations in an unsupervised fashion. Good data representations can substantially help the detection model to spot ...