#Machine Learning (ML)

Hi Community,

We're pleased to invite you to the upcoming webinar in Spanish called "IntegratedML - Creating ML models in minutes"!

Date & Time: September 30, 4:00 PM (CEST)

Speaker: @Eduardo Anglada, Sales Engineer, InterSystems Iberia

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

Hi Community,

Please welcome the new video, specially recorded by @Renato Banzai for the InterSystems IRIS AI Programming Contest:

⏯ IRIS ML Suite Demo

https://www.youtube.com/embed/3-YSnFQnMLU
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Hi Community,

Please welcome the new video from #VSummit20:

⏯ Showcasing Health Insight & IntegratedML for Healthcare Applications

https://www.youtube.com/embed/q8lC2a6eFgY
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This is the second post of a series explaining how to create an end-to-end Machine Learning system.

Exploring Data

The InterSystems IRIS already has what we need to explore the data: an SQL Engine! For people who used to explore data in
csv or text files this could help to accelerate this step. Basically we explore all the data to understand the intersection
(joins) which should help to create a dataset prepared to be used by a machine learning algorithm.

What is Distributed Artificial Intelligence (DAI)?

Attempts to find a “bullet-proof” definition have not produced result: it seems like the term is slightly “ahead of time”. Still, we can analyze semantically the term itself – deriving that distributed artificial intelligence is the same AI (see our effort to suggest an “applied” definition) though partitioned across several computers that are not clustered together (neither data-wise, nor via applications, not by providing access to particular computers in principle). I.e., ideally, distributed artificial intelligence should be arranged in such a way that none of the computers participating in that “distribution” have direct access to data nor applications of another computer: the only alternative becomes transmission of data samples and executable scripts via “transparent” messaging. Any deviations from that ideal should lead to an advent of “partially distributed artificial intelligence” – an example being distributed data with a central application server. Or its inverse. One way or the other, we obtain as a result a set of “federated” models (i.e., either models trained each on their own data sources, or each trained by their own algorithms, or “both at once”).

Hi Community!

Please welcome a new video on InterSystems Developers YouTube Channel:

Alexa: Connect Me with the World of IoT

https://www.youtube.com/embed/ZGYIdCTEqoQ
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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,

Please welcome the new video on InterSystems Developers YouTube:

⏯ Getting Started with IntegratedML

https://www.youtube.com/embed/f7A-wbNkIic
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Hey Community,

Play the new video on InterSystems Developers YouTube:

⏯ Unleashing the Power of Machine Learning with InterSystems @ Global Summit 2023

https://www.youtube.com/embed/X5VqUGVFcdM
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Hi Community!

Two more new videos are already on InterSystems Developers YouTube Channel:

1. Machine Learning - How it Works - Part 1

https://www.youtube.com/embed/47M8FWB5C5Y
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2. Machine Learning - How it Works - Part 2

Hi Developers,

Please welcome the new video, specially recorded by @José Pereira for the InterSystems IRIS AI Programming Contest:

⏯ Monitoring your ML model with IntegratedML

https://www.youtube.com/embed/KUjcpp5_a0w
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