Anomaly Detection of Time Series Data Using Machine Learning & Deep Learning

Time Series is defined as a set of observations taken at a particular period of time. For example, having a set of login details at regular interval of time of each user can be categorized as a time series. On the other hand, when the data is collected at once or irregularly, it is not taken as a time series data. Stock Series - It is a measure of attributes at a particular point in time and taken as a stock takes. Flow Series - It is a measure of activity at a specific interval of time. It contains effects related to the calendar. Time series is a sequence that is taken successively at the equally pace of time. It appears naturally in many application areas such as economics, science, environment, medicine, etc. There are many practical real life problems where data might be correlated with each other and are observed sequentially at the equal period of time.