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 everyone. 
We are a team of company  "Constructor" and we develop cutting edge cartographic systems. Recently the amount of image data skyrocketed so we want to give our users the ability to tie images to places automatically. For that, we want to use AI/ML technologies and we have a cool task for you.

https://cloud.mail.ru/public/pHbC/4r7Z58m6f/

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Hi Developers!

Here in Developers Community, we have posts, which are categorized by tags. Tags - are specific topics, which relate to InterSystems products, InterSystems services, or any concept related to software development, deployment, or maintenance etc. 

Tag is a helpful thing because it gives the option to follow/subscribe to the tag, filter the search by the tag,  understand how popular or not unpopular the topic and more.

And we have a problem!

Actually two problems. The tags for the post are selected by the author of the post, and we have the following issues: the author chooses wrong tags for a post, and the post lacks proper tags.

And we think this problem could be solved with AI/ML approach and so we suggest you solve it during the InterSystems IRIS AI Contest.

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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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Keywords:  PyODBC, unixODBC, IRIS, IntegratedML, Jupyter Notebook, Python 3

 

Purpose

A few months ago I touched on a brief note on "Python JDBC connection into IRIS", and since then I referred to it more frequently than my own scratchpad hidden deep in my PC. Hence, here comes up another 5-minute note on how to make "Python ODBC connection into IRIS".

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Preview releases are now available for InterSystems IRIS Advanced Analytics, and InterSystems IRIS for Health Advanced Analytics! The Advanced Analytics add-on for InterSystems IRIS introduces IntegratedML as a key new feature.

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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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Announcement
James Breen · 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 @Donald Woodlock, InterSystems VP of HealthShare Platforms.

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Hi everyone,

I am very pleased to announce that the Readmission Demo has been released as open source. Many thanks to the Solution Factory team that worked hard on making this possible.

Here are the changes:

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InterSystems IRIS ML Toolkit adds the power of InterSystems IntegratedML to further extend convergent scenario coverage into the area of automated feature and model type/parameter selection. The previous "manual" pipelines now collaborate within the same analytic process with "auto" pipelines that are based on automation frameworks, such as H2O.

Automated classification modeling in InterSystems IRIS ML Toolkit

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