Get a glimpse of future using time series forecasting using Auto-ARIMA and Artificial IntelligenceVeer KhotBlockedUnblockFollowFollowingDec 14AI and futureCurrently, there is a lot of development going on in Artificial intelligence research to get an accurate glimpse of the future..If any mathematical model predicts future data taking input as only time then that terminology called as time series forecasting..There are many machine learning and deep learning algorithms which can perform time series predictions like LSTM and ARIMA..Before going into technical part we will see the need of time series forecasting.The need of Time Series ForecastingWhen it comes to time series forecasting everyone’s dream is predict stock prices and become rich in one day..But there are lots of other important applications of time series forecasting some of them are listed below,Risk ManagementIn short in any small or big business risk management is very important..Which means if any company know when unplanned and unwanted events will occur they can manage the resources accordingly to avoid loss..For example, suppose a company wants to know how much attrition will happen in next month or next quarter so that they can allocate essential human resources required..This will saves the companies time and resources.Climate changePredicting climate change is one of the most important applications of time series forecasting because we can manage unwanted natural disasters like floods, drought, volcano eruptions, etc..In short, we can save millions of lives using time series forecasting.What is ARIMA?ARIMA is an acronym that stands for AutoRegressive Integrated Moving Average..This is one of the easiest and effective machine learning algorithm to performing time series forecasting..This is the combination of Auto Regression and Moving average..First, let’s understand AR part of ARIMA.. More details