It turns out that deep learning, with all its power, can also help with forecasting. Especially the LSTM (Long Short Term Memory) model, which proved to be useful while solving problems involving sequences with autocorrelation.
xgboost, or Extreme Gradient Boosting is a very convenient algorithm that can be used to solve regression and classification problems. You can check may previous post to learn more about it. It turns out we can also benefit from xgboost while doing time series predictions.
Data forecasting is a process of estimating the future based on historical values. It is described by time series, which is simply a series of time dependent data points. We usually forecast different costs or sales over time. We can try to predict weather conditions or model stock changes. Basically look at any process that can be described as time dependent with certain time interval (hourly, daily, monthly…).
R has a nice package support when it comes to forecasting. There is the forecast package which allows you to build several types of models