IntegratedML

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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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Keywords:  IRIS, IntegratedML, Machine Learning, Covid-19, Kaggle 

Continued from the previous Part I ... In part I, we walked through traditional ML approaches on this Covid-19 dataset on Kaggle. 

In this Part II, let's run the same data & task, in its simplest possible form, through IRIS integratedML which  is a nice & sleek SQL interface for backend AutoML options. It uses the same environment. 

 

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Hi Community!

We're pleased to invite you to the Online Meetup with the Winners of the InterSystems IRIS AI Programming Contest!

Date & Time: Friday, July 24, 2020 – 11:00 EDT

What awaits you at this virtual Meetup? 

  • Our winners' bios.
  • Short demos on their applications.
  • A short interview with all the winners about the past contest. Plans for the next contests.

 

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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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Currently, the process of using machine learning is difficult and requires excessive consumption of data scientist services. AutoML technology was created to assist organizations in reducing this complexity and the dependence on specialized ML personnel.

AutoML allows the user to point to a data set, select the subject of interest (feature) and set the variables that affect the subject (labels). From there, the user informs the model name and then creates his predictive or data classification model based on machine learning.

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Now Sapphire enable you load CSV to IRIS. See the steps:

1) Create a sample CSV file using Excel (save file as CSV):

2) Follow these instructions to install Sapphire into your enviroment: https://openexchange.intersystems.com/package/SAPPHIRE

3) Access Sapphire web page. Go to top menu Import > Load CSV

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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 Intersystem 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.

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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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In Episode 11 of Data Points, UX designer @Ksenia Samokhvalova joins the podcast to talk about the approach to user experience at InterSystems, how it may differ from commonly considered UX concepts, and what her team is doing to constantly improve usability with the developer's goals in mind. If you'd like to take a quick survey to get involved with UX testing for InterSystems technologies, you can do that here!

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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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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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You may have seen earlier this week that we launched a brand-new learning podcast called Data PointsThere 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!

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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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