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#IntegratedML

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InterSystems IntegratedML is an all-SQL machine learning (ML) module for InterSystems IRIS or IRIS for Health that:
- Gives users the ability to create, train and deploy powerful models from simple SQL syntax without requiring data scientists.
- Wraps "best of breed" open source and proprietary "AutoML" frameworks including DataRobot.
- Focuses on easy deployment to IRIS, so you can easily add machine learning to your applications.

Please find more information including videos and infographics at the IntegratedML Resource Guide.

Hi Developers!

Here're the technology bonuses for the InterSystems Vector Search, GenAI, and ML contest 2024 that will give you extra points in the voting:

  • Vector Search usage - 5
  • IntegratedML usage - 3
  • Embedded Python - 3
  • LLM AI or LangChain usage: Chat GPT, Bard, and others - 3
  • Questionnaire - 2
  • Docker container usage - 2
  • ZPM Package deployment - 2
  • Online Demo - 2
  • Implement InterSystems Community Idea - 4
  • Find a bug in Vector Search, or Integrated ML, or Embedded Python - 2
  • First Article on Developer Community - 2
  • Second Article On DC - 1
  • First Time Contribution - 3
  • Video on YouTube - 3
  • Suggest a new idea - 1

See the details below.<--break->

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Hi all,

Some days ago, I've seen a youtuber talking about how to create a neural network (sorry, is in spanish)

https://www.youtube.com/embed/iX_on3VxZzk
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Hi Community,

Play the new video on InterSystems Developers YouTube:

⏯ FHIR to IntegratedML - Can You Get There From Here @ Global Summit 2023

https://www.youtube.com/embed/L5sl1tbyJGY
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Introduction

In InterSystems IRIS 2024.3 and subsequent IRIS versions, the AutoML component is now delivered as a separate Python package that is installed after installation. Unfortunately, some recent versions of Python packages that AutoML relies on have introduced incompatibilities, and can cause failures when training models (TRAIN MODEL statement). If you see an error mentioning "TypeError" and the keyword argument "fit_params" or "sklearn_tags", read on for a quick fix.

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