TIM for Data Scientists | Tangent Works - Advanced Forecasting

TIM for Data Scientists

In this mini-series, we explain how TIM helps to solve challenges for multiple business roles. This article illustrates how TIM solves the challenges data scientists are facing.

 

TIM for Data Scientists Time-series forecasting

 

The Challenge: improving your productivity so you can focus on the most important tasks

 

It’s hard to recruit and retain data scientists these days. With a long list of potential AI use cases in your company, you may not be able to get the help you need to scale up the use of predictive analytics beyond a small number of projects.

 

TIM delivers scalable, automated, understandable AI

 

TIM improves your productivity by eliminating repetitive, trial-and-error modeling tasks and by helping you visualize your model with an intuitive heat map that shows the relative influence of all your input variables. Unlike other modeling tools that require you to choose from hundreds of pre-defined models, TIM creates an optimized model based on the patterns it detects in your time-series data. You’ll spend less time doing feature engineering, building and explaining models and more time on exploiting the power of predictive analytics across your organization.

 

Learn more about TIM InstantML →

 


 

Executives

Provides you with timely, accurate forecasts that help avoid the costs associated with system imbalances, reduce system downtime and optimize maintenance cycles. Read more.

 

Business Analyst

Automates the model generation process so you can create and update predictive models without being an AI expert. Read more.

 

Data Scientist

Improves your productivity by eliminating repetitive modeling tasks and clarifying the rationale behind predictions with understandable AI. 

 

IT Professionals

Compute-efficient, secure and flexible deployment in Azure or AWS Cloud, on-premise or on the edge. Easy to integrate in with your existing databases, BI tools and enterprise applications. Read more.

 

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