#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.

Hey Developers,

Good news! One more upcoming in-person event is nearby.

We're pleased to invite you to join "J On The Beach", an international rendezvous for developers and DevOps around Big Data technologies. A fun conference to learn and share the latest experiences, tips & tricks related to Big Data technologies, and, the most important part, it’s On The Beach!

🗓 April 27-29, 2022

📍Málaga, Spain

This year, InterSystems is a Gold Sponsor of the JOTB.

We're more than happy to invite you and your colleagues to our InterSystems booth for a personal conversation. As always, there will be some surprises on it... 😁

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Hi Community,

Don't miss the new video on InterSystems Developers YouTube:

⏯ Exploring Machine Learning with R Language Gateway

https://www.youtube.com/embed/GcN2wD-3FnA
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Hi Community,

Please welcome the new video on InterSystems Developers YouTube:

⏯ Machine Learning with IntegratedML & Data Robot

https://www.youtube.com/embed/BRyWD39Sado
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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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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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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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Keywords: IRIS, IntegratedML, Machine Learning, Covid-19, Kaggle

Purpose

Recently I noticed a Kaggle dataset for the prediction of whether a Covid-19 patient will be admitted to ICU. It is a spreadsheet of 1925 encounter records of 231 columns of vital signs and observations, with the last column of "ICU" being 1 for Yes or 0 for No. The task is to predict whether a patient will be admitted to ICU based on known data.

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Hi Developers,

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

⏯ Introducing Analytic Workflows

https://www.youtube.com/embed/i32l5ayptaQ
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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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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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A few months ago, I read this interesting article from MIT Technology Review, explaing how COVID-19 pandemic are issuing challenges to IT teams worldwide regarding their machine learning (ML) systems.

Such article inspire me to think about how to deal with performance issues after a ML model was deployed.

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Hi Community!

We are pleased to invite all the developers to the upcoming InterSystems AI Programming Contest Kick-Off Webinar! The topic of this webinar is dedicated to the InterSystems IRIS AI Programming Contest.

On this webinar, we will talk and demo how to use IntegratedML and PythonGateway to build AI solutions using InterSystems IRIS.

Date & Time: Monday, June 29 — 11:00 AM EDT

Speakers:
🗣 @Thomas Dyar, Product Specialist - Machine Learning, InterSystems
🗣 @Eduard Lebedyuk, Sales Engineer, InterSystems

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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!

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You may have seen earlier this week that we launched a brand-new learning podcast called Data Points! There are three episodes released, one of which was a really interesting discussion with Thomas Dyar — a product specialist here at InterSystems focused on machine learning. Take a listen and reach out if you're interested in exploring more about IntegratedML!

https://5e18edf067eb59-03854285.castos.com/player/147143
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Hi Community,

Enjoy watching the new video on InterSystems Developers YouTube Channel:

⏯ Machine Learning 301: Learning from Text

https://www.youtube.com/embed/PnguSWTGngw
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We're back with more AI, more ML and more presenters!

We are pleased to invite you to the upcoming webinar in English: AI Robotization (Python, R, Interoperability) for InterSystems IRIS on November 7 at 11:00 EST!

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Announcement
· Sep 12, 2019
Python Gateway 0.8 release

I'm happy to announce the latest Python Gateway release.

This is not an InterSystems product, it is community supported open source project.

Download new release from GitHub.

Now for the new features.

Fast transfer. Pass globals, classes and tables from InterSystems IRIS to Python with ease and speed (10x faster than old QueryExecute). Documentation.

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Hey Community!

The latest webinar, recorded by InterSystems Sales Engineers @Sergey Lukyanchikov and @Eduard Lebedyuk, is already on InterSystems Developers YouTube! Please welcome:

"Machine Learning Toolkit (Python, ObjectScript, Interoperability, Analytics) for InterSystems IRIS"

https://www.youtube.com/embed/z9O0F1ovBUY
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Article
· Apr 8, 2019 4m read
Should we use computers?

The titular question was quite relevant and often discussed some thirty years ago. The thought went: “Sure, there are industries where computers are the norm, but in my industry we got just fine so far, the benefits are questionable, problems innumerable and unsolved. Can we continue as before or should we embrace this new technology?”

Today, everyone asks the same question but about Machine Learning and Artificial Intelligence. The doubts are the same – lack of expertise, lack of known path, perceived irrelevancy to the industry.

Yet, as before, the correct, even the only possible answer is a resounding yes. Read on to find out why.

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Hi Everyone!

Very soon, almost every product and application will include artificial intelligence (AI).

On the afternoon of Wednesday, October 3, at the Global Summit 2018 in San Antonio we’re pulling together experts from InterSystems and from the front lines of the AI industry to discuss the current and future state-of-the-art for AI solutions.

Learn more about our Post-Summit Symposium: Artificial Intelligence and Machine Learning.

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With the release of InterSystems IRIS, we're also making available a nifty bit of software that allows you to get the best out of your InterSystems IRIS cluster when working with Apache Spark for data processing, machine learning and other data-heavy fun. Let's take a closer look at how we're making your life as a Data Scientist easier, as you're probably already facing tough big data challenges already, just from the influx of job offers in your inbox!

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