Featured Materials

In English

Breaking News:

Agent IRIS*

*In-Platform Agent-Based Simulation of a Connected Factory Cluster

In this paper we prototype and explore how multiple agent-based models of robotic factories connected to other robotic factories (represented by their respective models) can be orchestrated using an all-purpose data platform – thereby simulating descriptive and predictive properties of a group of factories (a factory cluster). For the underlying prototype, NetLogo suite was used to do factory agent-based simulation (re-using “Robotic Factory” model [1]) while InterSystems IRIS data platform was used for NetLogo orchestration and factory/cluster end-to-end simulation.

Webinars

• Online Meetup with the InterSystems AI Contest Winners on July 30th, 2021
• AI+ML Summit Convergent Analytics – Healthcare Stream on February 3rd, 2021
• AI+ML Summit Convergent Analytics – Cross-Industry Stream on January 28th, 2021
• Best Practices of In-Platform AI/ML on April 28th, 2020
• AI Robotization (Python, R, Interoperability) for InterSystems IRIS on November 7th, 2019
• Machine Learning Toolkit (Python, R, ObjectScript, Interoperability, Analytics) for InterSystems IRIS on April 23rd, 2019

Articles

• Distributed Artificial Intelligence with InterSystems IRIS as of April 3rd, 2021
• InterSystems IRIS – the All-Purpose Universal Platform for Real-Time AI/ML as of September 20th, 2020
• AI Robotization with InterSystems IRIS Data Platform as of December 5th, 2019
• MLOps can help overcome risk in AI and ML projects as of October 30th, 2019
• Python Gateway as of 12 April 2019

Collaboration Experiences

• An ML Toolkit for InterSystems IRIS: Co-Innovation in Healthcare on September 25th, 2019
• An ML Toolkit for InterSystems IRIS: Co-Innovation In Banking on September 24th, 2019
• Operationalizing Machine Learning: Experiences from the Field on September 23rd, 2019

Tutorials

• Learn IntegratedML in InterSystems IRIS on June 1st, 2020
• Predictive Modeling with the Machine Learning Toolkit on September 23rd and 25th, 2019

Demos

• ESKLP on July 12th, 2020 | Acknowledgements: Aleksandr Kalinin, Software Engineer, Escape, Russia
• Machine Learning Made Easy - Advanced Exercise on July 6th, 2020
• integratedml-demo-template on June 15th, 2020
• PythonGateway-Template on May 29th, 2020
• InterSystems IRIS Machine Learning Experience on November 12th, 2019

In German

Breaking News:

Mit der Schlange in die Produktion: Python für (I)IoT-Anwendungen

Python gilt als eine der beliebtesten Programmiersprachen von Entwicklern. Doch beim Datenbankzugriff und bei der Performance weist Python einige Nachteile auf. Abhilfe versprechen Lösungen, die Python näher an das eigentliche Herz von Anwendungen – die Daten – rücken. Welche Vorteile sich dadurch ergeben und was sich hinter „Embedded Python“ konkret verbirgt, erfahren Sie in diesem Webcast.

Webinars

• Wie Machine Learning zu Advanced Analytics führt on August 9th, 2019
• Machine Learning Projekte mit R erfolgreich umsetzen on August 2nd, 2019
• Machine Learning Projekte mit Python erfolgreich umsetzen on July 26th, 2019

In Russian

Breaking News:

Эксперимент IRIS

Платформенная агентная модель производственного кластера

В данной публикации мы описываем прототип и исследуем оркестровку нескольких агентных моделей связанных друг с другом роботизированных фабрик (представленных каждая своей моделью) с применением универсальной платформы данных – добиваясь симуляции наблюдаемых и прогнозных свойств группы фабрик (производственного кластера). В прототипе были задействованы программный комплекс NetLogo для агентных моделей фабрик (с моделью «Robotic Factory» [1] в качестве основы) и платформа данных InterSystems IRIS для оркестровки NetLogo и сквозной симуляции системы «фабрики-кластер».

Webinars

• Лучшие практики платформенного AI/ML on April 10th, 2020 | Acknowledgements: Aleksandr Kalinin, Software Engineer, Escape, Russia
• InterSystems ML Toolkit: роботизация искусственного интеллекта on September 18th, 2019
• Machine Learning Toolkit (Python, R, ObjectScript, Interoperability, Analytics) для InterSystems IRIS on March 26th, 2019

Articles

• Распределенный искусственный интеллект на платформе InterSystems IRIS as of March 26th, 2021
• InterSystems IRIS – универсальная AI/ML-платформа реального времени as of August 24th, 2020
• Python Gateway в InterSystems IRIS as of February 5th, 2020
• Роботизация искусственного интеллекта на платформе InterSystems IRIS as of October 28th, 2019

In French

Breaking News:

Comment construire et mettre en œuvre une stratégie Data Driven ?

Améliorer vos processus opérationnels ou prendre les bonnes décisions, la donnée s’impose comme un actif précieux et indispensable dans l’élaboration et la mise en œuvre d’une stratégie d’entreprise Data Driven. Pourquoi et comment mettre en place une stratégie Data Driven et avec quelles technologies ? Autant de questions abordées lors de cette prise de parole qui fera le point sur les bonnes pratiques à travers l’intervention d’experts et de témoignages clients dans la mise en place d’une stratégie Data Driven réussie.

Webinars

• Comment réduire le temps du Build et augmenter la performance du Run ? on May 26th, 2021 | Acknowledgements: Sani Imini, Manager Data, DataValue Consulting, France and Mélanie Froment, Responsable SI Corporate, CFAO, France
• Digital SCE on December 8th, 2020 | Acknowledgements: Blaise Zarka, Technology Architect, snext, France

Links to Required Downloads

• InterSystems IRIS Community Edition: download a community edition of InterSystems IRIS data platform here - create an account to start the download
• ML Toolkit: Python Gateway: download an open-source set of extensions to InterSystems IRIS for in-platform orchestration of Python here
• ML Toolkit: R Gateway: download an open-source set of extensions to InterSystems IRIS for in-platform orchestration of R here
• ML Toolkit: Julia Gateway: download an open-source set of extensions to InterSystems IRIS for in-platform orchestration of Julia here

Repository Resources Legend

• Programs: program classes for pre-configured showcases
• Data: source data for showcases
• Tables: table classes for showcases

Root Resources

• Download the illustrated ML Toolkit learning guide here - for the most recent documentation and showcases, consider joining the private dedicated ML Toolkit repo by writing us
• Check how to edit BPL annotations here
• Check how to disable journaling here
• Check how to disable auto-refresh here
• AI+ Playlist from Virtual Summit 2021
• AI+ Playlist from Virtual Summit 2020

Showcases (Programs/Data/Tables):

• 000 Robotized ML - FACTORY.xml/FACTORY.zip/FACTORY.txt
• 001 Sentiment Analysis - SENTIMENT.cls/SENTIMENT_NEG_UTF8.txt, SENTIMENT_POS_UTF8.txt, SENTIMENT_UNK_UTF8.txt/SENTIMENTNEG.cls, SENTIMENTPOS.cls, SENTIMENTUNK.cls
• 002 Engine Condition Classification - ENGINES.cls/ENGINES_EVEN.txt, ENGINES_ODD.txt/ENGINESEVEN.cls, ENGINESODD.cls
• 003 Reimbursement Request Check - RECORD.cls/RECORD_TEST.txt, RECORD_TRAIN.txt/RECORDTEST.cls, RECORDTRAIN.cls
• 004 Retail Cannibalization Analysis - CANNIBALIZATION.cls/CANNIBALIZATION.txt/CANNIBALIZATIONVOLUMEYEARWEEKCATEGORYDESC.cls
• 005 Marketing Campaign Optimization - CAMPAIGN.cls/CAMPAIGN_APPLY.txt, CAMPAIGN_TRAIN.txt/CAMPAIGNAPPLY.cls, CAMPAIGNTRAIN.cls
• 006 Rail Time Series Discovery - INTRA.cls/INTRA.txt
• 007 Housing Debts Prediction - HOUSING.cls/HOUSING_TEST.txt, HOUSING_TRAIN.txt/HOUSINGTEST.cls, HOUSINGTRAIN.cls
• 008 Diseases Network Analysis - DISEASES.cls/DISEASES_MATRIX.txt, DISEASES_NODES.txt/DISEASESMATRIX.cls, DISEASESNODES.cls