#Machine Learning (ML)

Hi Community,
In this article, I will introduce my application iris-mlm-explainer

Bring your laptop to the Experience Lab on Global Summit 2018 and engage with our technologies in a whole new way!

Fixing the terminology

A robot is not expected to be either huge or humanoid, or even material (in disagreement with Wikipedia, although the latter softens the initial definition in one paragraph and admits virtual form of a robot). A robot is an automate, from an algorithmic viewpoint, an automate for autonomous (algorithmic) execution of concrete tasks. A light detector that triggers street lights at night is a robot. An email software separating e-mails into “external” and “internal” is also a robot. Artificial intelligence (in an applied and narrow sense, Wikipedia interpreting it differently again) is algorithms for extracting dependencies from data. It will not execute any tasks on its own, for that one would need to implement it as concrete analytic processes (input data, plus models, plus output data, plus process control). The analytic process acting as an “artificial intelligence carrier” can be launched by a human or by a robot. It can be stopped by either of the two as well. And managed by any of them too.

This is the third post of a series explaining how to create an end-to-end Machine Learning system.

Training a Machine Learning Model

When you work with machine learning is common to hear this work: training. Do you what training mean in a ML Pipeline?
Training could mean all the development process of a machine learning model OR the specific point in all development process
that uses training data and results in a machine learning model.

Hi Community,

We're pleased to invite you to the online meetup with the winners of the InterSystems AI contest!

Date & Time: Friday, July 30, 2021 – 11:00 AM EDT

What awaits you at this Virtual Meetup?

• Our winners' bios.
• Short demos on their applications.
• An open discussion about technologies being used. Q&A. Plans for the next contests.

https://www.youtube.com/embed/27vE9o9U3nM
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Hi Community

In this article, I will introduce my application IRIS-GenLab.

IRIS-GenLab is a generative AI Application that leverages the functionality of Flask web framework, SQLALchemy ORM, and InterSystems IRIS to demonstrate Machine Learning, LLM, NLP, Generative AI API, Google AI LLM, Flan-T5-XXL model, Flask Login and OpenAI ChatGPT use cases.

Hi Community:

If you're interested in the future of InterSystems technology, you won't want to miss these nine Global Summit sessions on our hottest technologies:

Roadmap Sessions

Hey Developers,

Please welcome the new session recording from the InterSystems AI+ML Summit 2021:

⏯ AI+ML Summit Convergent Analytics – Cross-Industry Stream

https://www.youtube.com/embed/rRJ8_O4Y3gs
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Hi Community,

The new video from Global Summit 2019 is already on InterSystems Developers YouTube:

⏯ InterSystems IRIS Roadmap: Analytics and AI

https://www.youtube.com/embed/W2zvl3BO1lA
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Hi developers!

We are starting InterSystems AI Programming Contest next week, and according to the rules, you can include some technology IRIS Features into your solutions, which will give you extra points in the voting.

Here are the technology bonuses for InterSystems AI Programming Contest!

1. IntegratedML usage - 2 expert vote points

IntegratedML is a new technology Introduced in InterSystems IRIS which you can use with InterSystems IRIS 2020.2 Advanced Analytics Preview release. IntegratedML:

• 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.

Learn more in IntegratedML Resource Guide.

You can use with IntegratedML template.

2. Python Gateway usage - 1 expert vote point

Python Gateway is an addon to InterSystems IRIS which gives you the way to use Python in InterSystems IRIS environment:

• Execute arbitrary Python code.
• Seamlessly transfer data from InterSystems IRIS into Python.
• Build intelligent Interoperability business processes with Python Interoperability Adapter.
• Save, examine, modify and restore Python context from InterSystems IRIS.

Learn more about Python Gateway.

You can use the Python Gateway template, which includes IntegratedML too.

3. Docker container - 1 expert vote point

The application gets a 'Docker container' bonus if it uses InterSystems IRIS running in a docker container.

Both templates, IntegratedML template and Python Gateway template use docker so you can collect this bonus if you build your solution using these templates.

Or you can use any other Docker-based templates, published on Open Exchange.

Feel free to ask any questions about using the listed technologies.

Good luck in the competition!

Hi community members!

I'm trying to deploy a container based on IRIS Community for Health ML image available from this url but when I start the container the memory consumption skyrockets to 99% making impossible to work with the instance (it never goes below the 95% of the memory). When I do the same with the IRIS Community for Health image it never goes over 80% of memory.

Hi Community,

This week we have two new videos from Global Summit 2019. Please welcome:

1. An ML Toolkit for InterSystems IRIS: Co-Innovation in Healthcare

https://www.youtube.com/embed/o0T0AgvxaNk
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Hey Developers,

This week is a voting week for the InterSystems Analytics Contest! So, it's time to give your vote to the best solutions built with InterSystems IRIS.

🔥 You decide: VOTING IS HERE 🔥

How to vote?

Please meet the new voting engine and algorithm for the Experts and Community nomination: