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#Machine Learning (ML)

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Machine learning (ML) is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to "learn" with data, without being explicitly programmed.

Learn more.

Announcement
· Aug 30, 2018
Machine Learning 101 Presentation

View Machine Learning 101 recording at: https://videos.intersystems.com/detail/video/5827774460001/machine-learning-101?autoStart=true&q=machine%20learning.

In addition to our webinar on machine learning (https://community.intersystems.com/post/rescheduled-webinar-its-machine-learning-not-rocket-science-july-31-1100-am-edt), we are pleased to announce a basic introduction to machine learning presentation that provides an overview of the basic algorithms by @Don Woodlock, InterSystems VP of HealthShare Platforms.

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Article
· Jan 16, 2020 2m read
Python Gateway VI: Jupyter Notebook

This series of articles would cover Python Gateway for InterSystems Data Platforms. Execute Python code and more from InterSystems IRIS. This project brings you the power of Python right into your 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

Other articles

The plan for the series so far (subject to change).

Intro

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.

This extension allows you to browse and edit InterSystems IRIS BPL processes as jupyter notebooks.

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Whats NLP Stands For?

NLP stands for Natural Language Processing which is a field of Artificial Intelligence with a lot of complexity and
techniques to in short words "understand what are you talking about".

And FHIR is...???

FHIR stands for Fast Healthcare Interoperability Resources and is a standard to data structures for healthcare. There are
some good articles here explainig better how FHIR interact with Intersystems IRIS.

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Hey Developers,

New "Coding Talk" video was specially recorded by @Yuri Marx for the InterSystems IRIS AI Programming Contest:

⏯ SAPPHIRE - AutoML UI to InterSystems IntegratedML

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

Enjoy watching the new session recording from the InterSystems AI+ML Summit 2021:

⏯ AI+ML Summit Convergent Analytics – Healthcare Stream

https://www.youtube.com/embed/yDRZwK3maeQ
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In our latest episode of Data Points, I had a conversation with @Thomas Dyar about AI Link, which helps bridge the gap between data scientists and business analysts. Our conversation talks about how AI Link fits with IntegratedML and Adaptive Analytics, as well, as what new features are on the horizon for IntegratedML. Take a listen!

https://5e18edf067eb59-03854285.castos.com/player/1346398
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Hey Developers,

See how InterSystems IRIS Adaptive Analytics can be used to aggregate and query billions of records from a virtual cube, applying machine learning and analytics to that data.

⏯ InterSystems IRIS Adaptive Analytics in Action

https://www.youtube.com/embed/BCV1v91iZwk
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Hi Developers,

Please welcome the new video, specially recorded by @Zhong.Li for the InterSystems IRIS AI Programming Contest:

⏯ IntegratedML-Template Demo

https://www.youtube.com/embed/YxpMc3sODxk
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Hi Community!

Enjoy watching the new video on InterSystems Developers YouTube and learn more about IntegratedML feature:

⏯ IntegratedML: Predicting Readmissions

https://www.youtube.com/embed/aDo7PfmBnu8
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Hi Community!

Enjoy watching the new video on InterSystems Developers YouTube and learn about IntegratedML feature:

⏯ What is IntegratedML in InterSystems IRIS?

https://www.youtube.com/embed/N9QnVx_GLvk
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Hey Developers!

This week is a voting week for the InterSystems IRIS AI Programming Contest!

So, it's time to give your vote to the best AI- and ML-enabled solution on InterSystems IRIS!

🔥 You decide: VOTING IS HERE 🔥

How to vote? This is easy: you will have one vote, and your vote goes either in Experts Nomination or in Community Nomination.

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Hi Community,

We're pleased to invite you to join the upcoming InterSystems IRIS 2020.1 Tech Talk: Data Science, ML & Analytics on April 21st at 10:00 AM EDT!

In this first installment of InterSystems IRIS 2020.1 Tech Talks, we put the spotlight on data science, machine learning (ML), and analytics. InterSystems IntegratedMLTM brings automated machine learning to SQL developers. We'll show you how this technology supports feature engineering and chooses the most appropriate ML model for your data, all from the comfort of a SQL interface. We'll also talk about what's new in our open analytics offerings. Finally, we'll share some big news about InterSystems Reports, our "pixel-perfect" reporting option. See how you can now generate beautiful reports and export to PDF, Excel, or HTML.

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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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Thank you community for translating an earlier article into Portuguese.
Am returning the favor with a new release of Pattern Match Workbench demo app.

Added support for Portuguese.

The labels, buttons, feedback messages and help-text for user interface are updated.

Pattern Descriptions can be requested for the new language.

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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 Developers,

Please welcome the new video on InterSystems Developers YouTube:

⏯ Building Health IT Apps with Artificial Intelligence

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

Enjoy watching the new video on InterSystems Developers YouTube:

⏯ Introduction to AutoML @ Global Summit 2022

https://www.youtube.com/embed/X6Ji9x-y8x8
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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”).

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