OpenTox Virtual Conference 2020 Session 10: Data Science and AI Applications
Time Series Forecasting
Time series forecasting is an important area of machine learning that is often neglected. The topic is relevant nowadays because there are so many prediction problems that involve a time component. These problems are neglected because it is this time component that makes time series problems more difficult to handle. The skill of a time series forecasting model is determined by its performance at predicting the future. This is often at the expense of being able to explain why a specific prediction was made, confidence intervals and even better understanding the underlying causes behind the problem. The talk will focus on various time series forecasting techniques. The audience will gain an in depth understanding of various time series models, components of a time series, ways to handle stationarity, and the prediction techniques. Further, the introduction of ensemble modelling for predictive accuracy enhancement may be discussed.