Self-Supervised Learning for Anomaly Detection in Python: Part 2


Self-supervised learning is one of the most popular fields in modern deep-learning research. As Yann Lecun likes to say self-supervised learning is the dark matter of intelligence and the way to create common sense in AI systems. The ideas and techniques of this paradigm attract many researchers to try and enlarge the application of self-supervised learning into new research fields. Of course, anomaly detection is not an exception. In Part 1 of this article, we discussed the definition of anomaly detection and a technique called Kernel Density Estimation.

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