Ai+ Training

Building forecasts are an integral part of any business, whether it’s revenue, inventory, sales, or customer demand. Building machine learning models is time-consuming and complex with many factors to consider, such as iterating through algorithms, tuning your hyperparameters and feature engineering. These choices multiply with time-series data, with additional considerations of trends, seasonality, holidays, and effectively splitting training data. Forecasting with automated machine learning includes capabilities that improve the accuracy and performance of recommended models using techniques like rolling-origin cross-validation, configurable lags, deep learning models and much more. Join us to dive into automated machine learning and its extensive forecasting capabilities.