The Tangent Information Modeler builds high quality, explainable models on continuously evolving data in any circumstances. Predictive analytics for time series in use cases such as forecasting and anomaly detection. Right into your favourite data analytics solution without the need for any data scientist.
Getting information from data often is difficult and requires expertise. This is particularly true in time series analysis, because of its highly dynamic nature. Many usecases come down to forecasting with time series. This is exactly the subject in which TIM excell. Tangent Works reduces the need for valuable resources ( time, money, expertise) and helps users to leverage insights that are hidden in their data.
TIM automates feature engineering while many other modelling tools require manual feature engineering that requires a domain expert. This manual proces takes a long time, especially since the number of combinations grow exponentially with the number of input variables.
TIM's automation allows the enine to create models with equivalent or even better accuracy then the manually built models. And all this in a matter of minutes.
TIM is built to be efficient and can process huge datasets in minutes time. This means users can automatically create many models and update those models as frequently as desired. TIM helps companies to handle the increasing demand for predictive models by automating the most tedious aspects of model building.
Explaining the model(s) the people who depend on them is a great challenge of predictive modelling. TIM presents its models as an equivalence in a human-readable format, which can be visualised as a map that shows the weights of and relationships between the model’s input variables.
The architecture of the Tangent Information Modeller ( TIM) , is optimised for smooth integration with existing databases, BI tools and other enterprise applications. To realise this, all of TIM’s functionalities are easily accessible through its REST API. This structure also guarantees the utmost deployment flexibility.
This book is written primarily for nontechnical readers who don’t necessarily know a lot about the underlying technologies such as machine learning (ML) and artificial intelligence (AI).
Time-series data is everywhere. In industries from retail to finance and manufacturing to energy, companies try to use time-series data to deliver business value. But unfortunately, many machine learning projects never get past the experimentation stage as data scientists toil over handcrafted model building, testing, and tuning for days or weeks — far too long for businesses to leverage the information for real-time decisions.