Time Series Forecasting
Using AI in every level of operation has become the indispensable norm for multi-billion corporations since a decade. Even though most of the end users may not notice, AI algorithms currently orchestrate their everyday life. From recommendation systems to optimization of delivery services, securing automated bank transactions to accurately forecasting wind speed in future.
One of the important areas of AI is time series forecasting, a technique for predicting events through a sequence of time. It predicts future events by analyzing trends and patterns from the past. This future forecasting is a major concern in most industries for various purposes such as business planning, ressource allocation, inventory management, predictive maintenance, etc.
Predicting events through a sequence of time
Build your own forecasting models
Efficiently handle heteregenous time series
Maximize forecast accuracy
Discover interesting insights
What is the advantage of the time series
module on the papAI platform?
Our PapAI Timeseries forecasting module allows you to build your own forecasting models that solve your real-world challenges through just few clicks and with high forecasting accuracy.
Our goal is to bring the extreme precision of the latest state-of-the-art algorithms and AI concepts, where other platforms fail or are years behind. One of our strengths also is the capability to efficiently handle heteregenous time series from many sources and the ability to incorporate covariates to maximize forecast accuracy.
This Forecasting module is accompanied by two other modules that are equally important, Timeseries cleaning and Timeseries analysis. The former facilitates the process of cleaning and preparing the data before forecasting, and the latter allows you to discover some interesting insights
It is also possible to detect abnormal behavior in time series, by giving an anomaly score for each point in time.