#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.

In this article, I am trying to identify the multiple areas to develop the features we can able to do using python and machine learning.

Each hospital is every moment trying to improve its quality of service and efficiency using technology and services.

The healthcare sector is one of the very big and vast areas of service options available and python is one of the best technology for doing machine learning.

In every hospital, humans will come with some feelings, if this feeling will understand using technology is make a chance to provide better service.

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Hi community members!

I'm trying to deploy a container based on IRIS Community for Health ML image available from this url but when I start the container the memory consumption skyrockets to 99% making impossible to work with the instance (it never goes below the 95% of the memory). When I do the same with the IRIS Community for Health image it never goes over 80% of memory.

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Article
· Jul 27, 2018 4m read
Load a ML model into InterSystems IRIS

Hi all. Today we are going to upload a ML model into IRIS Manager and test it.

Note: I have done the following on Ubuntu 18.04, Apache Zeppelin 0.8.0, Python 3.6.5.

Introduction

These days many available different tools for Data Mining enable you to develop predictive models and analyze the data you have with unprecedented ease. InterSystems IRIS Data Platform provide a stable foundation for your big data and fast data applications, providing interoperability with modern DataMining tools.

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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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In this GitHub we fine tune a bert model from HuggingFace on review data like Yelp reviews.

The objective of this GitHub is to simulate a simple use case of Machine Learning in IRIS :
We have an IRIS Operation that, on command, can fetch data from the IRIS DataBase to train an existing model in local, then if the new model is better, the user can override the old one with the new one.
That way, every x days, if the DataBase has been extended by the users for example, you can train the model on the new data or on all the data and choose to keep or let go this new model.

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In the ever-evolving landscape of data science and machine learning, having the right tools at your disposal can make all the difference. In this article, we want to shine a spotlight on two essential Python libraries that have become indispensable for data scientists and machine learning practitioners alike: Matplotlib and scikit-learn.

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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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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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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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Hi Community,

We're pleased to invite you to the online meetup with the winners of the InterSystems AI contest!

Date & Time: Friday, July 30, 2021 – 11:00 AM EDT

What awaits you at this Virtual Meetup?

  • Our winners' bios.
  • Short demos on their applications.
  • An open discussion about technologies being used. Q&A. Plans for the next contests.

https://www.youtube.com/embed/27vE9o9U3nM
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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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Hi Community,

We're pleased to invite all the developers to the upcoming InterSystems AI Contest Kick-Off Webinar! The topic of this webinar is dedicated to the InterSystems AI programming contest.

During the webinar, we will demo how to load data into IRIS, how to deal with it using ODBC/JDBC and REST, and how to use special AI/ML features of IRIS: IntegratedML, DataRobot, R Gateway, Embedded Python, PMML.

Date & Time: Monday, June 28 — 11:00 AM EDT

Speakers:
🗣 @Aleksandar Kovacevic, InterSystems Sales Engineer
🗣 @Théophile.Thierry, InterSystems Intern
🗣 @Bob Kuszewski, Product Manager - Developer Experience, InterSystems
🗣 @Evgeny Shvarov, InterSystems Developer Ecosystem Manager

https://www.youtube.com/embed/4vC1gp1PeUw
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Hi Community!

We are pleased to invite you to the upcoming webinar "Machine Learning Toolkit (Python, ObjectScript, Interoperability, Analytics) for InterSystems IRIS" on 26th of March at 10:00 (Moscow time)!

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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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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 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,

Don't miss this hands-on session hosted by @Don Woodlock, Vice President of InterSystems Healthcare:

⏯ Machine Learning 201 - Neural Networks and Image Recognition

https://www.youtube.com/embed/lDRemLwc_U4
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As we all know, InterSystems is a great company.

Their products can be just as useful as they are complex.

Yet, our pride sometimes prevents us from admitting that we might not understand some concepts or products that InterSystems offers for us.

Today we are beginning a series of articles explaining how some of the intricate InterSystems products work, obviously simply and clearly.

In this essay, I will clarify what Machine Learning is and how to take advantage of it.... because this time, you WILL KNOW for sure what I am talking about.

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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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