Democratizing Machine Learning for Big Series

Informations projet

DEMABIS

N° de convention de subvention: 889633

DOI

10.3030/889633

Projet clôturé

Date de signature de la CE 13 Novembre 2019

Date de début 1 Decembre 2019

Date de fin 29 Février 2020

Financé au titre de

• INDUSTRIAL LEADERSHIP - Innovation In SMEs

Coût total

€ 71 429,00

Contribution de l’UE

€ 50 000,00

Coordonné par

GRUMPY CAT SOFTWARE SL
Spain

Periodic Reporting for period 1 - DEMABIS (Democratizing Machine Learning for Big Series)

Période du rapport: 2019-12-01 au 2020-02-29

Résumé du contexte et des objectifs généraux du projet

The major aim of the feasibility study is to assess the overall performance of Shapelets against other competing alternatives, strengthening the definition of our value proposition, while assessing the different market verticals and how to enter them. To have a successful market uptake and establish a leading position in time series analysis a rodmap for the next two years has been defined, and the acute need to perform different validations to become bankable identified.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

The Feasibility Study conducted ensured the technical, commercial and financial feasibility of the Shapelets suite. Shapelets has strengthened the definition of its value proposition, performed a benchmarking analysis against different market alternatives, analyzing the energy utilities market, and two specific segments of the industrial market to later aseess the financial needs to enter these markets, with a technology roadmap and staff growth strategy.

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

Shapelets is the first platform tailored for time series analysis. It provides the latest time series algorithms orginated from academia as well as the tools Data Scientists and decision makers need to make the most of data series. It provides the most complete set of tools for time series analysis which will enable important energy and resources savings for its customers, reducing the environmental impact of two markets that have an important weight on global CO2 emissions.

Shapelets time series analysis.