In the last decades, thanks to the advent of IoT (Internet of Things) and in general to the development of information technology, data have been doubling every year. Most of these data are collected in the form of Multivariate Time Series. The huge amount of time related information collected, allow us to monitor systems and identify deviations from the normal behavior, this is the well-known task of Anomaly Detection. Anomaly Detection is one of the most difficult tasks in Data Science due to issues and costs that needs to be afforded during the data collection and labelling processes. Anomaly Detection has been studied since the start of data science and statistics, but in the last years Deep learning advent opened the field of Deep Anomaly Detection and enabled the proliferation of more and more Nueral Network based algorithms which performances strictly depend on the nature of data.