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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1. Integrated ML Demonstration

This repository is a demonstration of IntegratedML and Embedded Python.

• 1. Integrated ML Demonstration
• 2. Building the demo
  • 2.1. Architecture
  • 2.2. Building the nginx container
• 3. Running the demo
• 4. Python back-end
  • 4.1. Embedded Python
  • 4.1.1. Setting up the container
  • 4.1.2. Using Embedded Python
  • 4.1.3. Side By Side Comparaison
  • 4.2. Launching the server
• 5. IntegratedML
  • 5.1. Exploring both datasets
  • 5.2. Managing models
  • 5.2.1. Creating a model
  • 5.2.2. Training a model
  • 5.2.3. Validating a model
  • 5.2.4. Making predictions
• 6. Using COS
• 7. More explainability with DataRobot
• 8. Conclusion

Hey Community,

Don't miss the latest videos on InterSystems Developers YouTube channel:

⏯ IntegratedML Update from the Field

https://www.youtube.com/embed/2-i2Z7aukSc
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Maternal Risk can be measured from some parameters well known to the medical community. In this way, in order to help the medical community and computerized systems, especially AI, the scientist Yasir Hussein Shakir published a very useful dataset for training ML algorithms in the detection/prediction of Maternal Risk.

Diabetes can be discovered from some parameters well known to the medical community. In this way, in order to help the medical community and computerized systems, especially AI, the National Institute of Diabetes and Digestive and Kidney Diseases published a very useful dataset for training ML algorithms in the detection/prediction of diabetes. This publication can be found on the largest and best known data repository for ML, Kaggle at https://www.kaggle.com/datasets/mathchi/diabetes-data-set.

The InterSystems IRIS IntegratedML feature is used to get predictions and probabilities using the AutoML technique. The AutoML is a Machine Learning technology used to select the better Machine Learning algorithm/model to predict status, numbers and general results based in the past data (data used to train the AutoML model). You don't need a Data Scientist, because the AutoML it will test the most common Machine Learning algorithms and select the better algorithm to you, based in the data features analysed. See more here, in this article.

Have you tried the InterSystems learning platform lab for IRIS IntegratedML? In that lab you can train and test a model on a readmission dataset and be able to predict when a patient will be readmitted or not, or calculate its probability of being readmitted.

You can try it without any installation on your system, all you have to do is start a virtual lab environment (Zeppelin) and play it around!

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

Talking with a friend of mine, Machine Learning specialist @Renato Banzai , he brought one of the biggest challenges faced by companies nowadays: deploying ML/AI in live environments.

Hi!

I'd like to know how to get feature importance after creating and training a model, using IntegratedML with AutoML provider?

Thanks!

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

Update: added support for regression model
Hi everyone!

In this brief article, I'll show you how to write an adapter for IRIS Interoperability for use ML models managed by IRIS IntegratedML.

Hi Community,

See how IntegratedML in InterSystems IRIS can be used to make machine learning predictions directly from SQL commands:

⏯ IntegratedML in a Nutshell

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.