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.
In InterSystems IRIS 2024.3 and subsequent IRIS versions, the AutoML component is now delivered as a separate Python package that is installed after installation. Unfortunately, some recent versions of Python packages that AutoML relies on have introduced incompatibilities, and can cause failures when training models (TRAIN MODEL statement). If you see an error mentioning "TypeError" and the keyword argument "fit_params" or "sklearn_tags", read on for a quick fix.
Article to announce pre-built pattern expressions are available from demo application.
AI deducing patterns require ten and more sample values to get warmed up.
The entry of a single value for a pattern has therefore been repurposed for retrieving pre-built patterns.
Paste an sample value for example an email address in description and press "Pattern from Description".
The sample is tested against available built-in patterns and any matching patterns and descriptions are displayed.
Why Randomization is Key When Splitting Data for Machine Learning
Post:
Essentially, Machine Learning is about learning from data. Having "good" data leads to better models, and more importantly, the quality of the information being used plays a crucial role in improving prediction accuracy.
One critical step in the process is how we separate our data into training and validation sets. If this isn’t done properly, we risk introducing bias, overfitting, or unrealistic performance expectations for the model.
In this article, we’ll explore:
Those curious in exploring new GenerativeAI usecases.
Shares thoughts and rationale when training generative AI for pattern matching.
A developer aspires to conceive an elegant solution to requirements.
Pattern matches ( like regular expressions ) can be solved for in many ways. Which one is the better code solution?
Can an AI postulate an elegant pattern match solution for a range of simple-to-complex data samples?
Consider the three string values:
Thank you community for translating an earlier article into Portuguese.
Am returning the favor with a new release of Pattern Match Workbench demo app.
Added support for Portuguese.
The labels, buttons, feedback messages and help-text for user interface are updated.
Pattern Descriptions can be requested for the new language.
The single AI Model for transforming user prompt into Pattern match code was fully retrained.
Previously, we trained our model using machine learning. However, the sample data we utilized was generated directly from insert statements.
Today, we will learn how to load this data straight from a file.
Introducing Smart Clinical Sidechick — the intelligent, no-drama partner your EHR wishes it could be. She reads FHIR data in real time, interprets lab results without ghosting, and explains clinical alerts like she actually cares. Built with GPT-4 brains and YAML sass, she’s not here to replace your main EHR—just to make it look bad. Tired of irrelevant alerts and cryptic warnings? Sidechick serves up real, explainable insights, not vague “elevated risk” vibes. And when your backend crashes, she doesn’t panic—she self-heals. Secure, responsive, and (unlike your last vendor) emotionally
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.
This article shares analysis in solution cycle for the Open Exchange application TOOT ( Open Exchange application )
A button on a web page can capture the users voice. IRIS integration could manipulate the recordings to extract semantic meaning that IRIS vector search can then offer for new types of AI solution opportunity.
The fun semantic meaning chosen was for musical vector search, to build new skills and knowledge along the way.
Overview
With the help of SQL, you can build, train, and manage machine learning models directly in the database with InterSystems IRIS's robust IntegratedML tool. Using SQL examples that represent your data, we will go over IntegratedML configuration and how it is used in practical situations in this article.
In today's data landscape, businesses encounter a number of different challenges. One of them is to do analytics on top of unified and harmonized data layer available to all the consumers. A layer that can deliver the same answers to the same questions irrelative to the dialect or tool being used. InterSystems IRIS Data Platform answers that with and add-on of Adaptive Analytics that can deliver this unified semantic layer. There are a lot of articles in DevCommunity about using it via BI tools. This article will cover the part of how to consume it with AI and also how to put some insights
Hi all,
Some days ago, I've seen a youtuber talking about how to create a neural network (sorry, is in spanish)
Hi Community,
In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):
So Let us start.
Hi Community,
Watch this video to learn about the PainChek artificial intelligence technology, which assesses patient pain at the hospital bedside, leverages InterSystems IRIS interoperability to connect to third-party electronic medical record systems:
Looking to get started with generative AI? Try two brand-new learning paths. In Getting Started with Generative AI (2h 45m), learn the basics of interacting with GenAI. Then, try Developing Generative AI Applications (2h) to start developing your own GenAI application. Plus, earn badges for completing each path!
Considering new business interest in applying Generative-AI to local commercially sensitive private data and information, without exposure to public clouds. Like a match needs the energy of striking to ignite, the Tech lead new "activation energy" challenge is to reveal how investing in GPU hardware could support novel competitive capabilities. The capability can reveal the use-cases that provide new value and savings.
Sharpening this axe begins with a functional protocol for running LLMs on a local laptop.
DNA Similarity and Classification was developed as a REST API utilizing InterSystems Vector Search technology to investigate genetic similarities and efficiently classify DNA sequences. This is an application that utilizes artificial intelligence techniques, such as machine learning, enhanced by vector search capabilities, to classify genetic families and identify known similar DNAs from an unknown input DNA.
K-mer Analysis: Fundamentals in DNA Sequence Analysis
Hey Community,
We have more exciting news! The new InterSystems online programming contest dedicated to Generative AI, Vector Search and Machine Learning is starting very soon!
🏆 InterSystems Vector Search, GenAI and ML Contest 🏆
Duration: April 22 - May 19, 2024
Prize pool: $14,000
Hey Community,
Play the new video on InterSystems Developers YouTube:
⏯ Unleashing the Power of Machine Learning with InterSystems @ Global Summit 2023
When trying to create a ML Model I ran into the problem, that AutoML apparantly isn't available on my IRIS instance.
I was able to use the following command successfully: CREATE MODEL ECLASSPREDICT PREDICTING (eClass) FROM SQLUSER.CRMSHOPARTIKEL
Then when trying to use TRAIN MODEL ECLASSPREDICT, I get the error from the image:
Roughly translates to : "-186: Modelprovider not available on this instance. #2822 %ML provider 'AutoML' is not available on this instance"
In my ML Configurations there are 3 standard configurations called %AutoML, %H20 and %PMML which I haven't changed.
Interested in predictive modeling? This exercise shows how IntegratedML® works, and you can get practice creating a model with sample patient data. Try it out and share what you think!
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.
.png)
Hi Community
In this article, I will introduce my application IRIS-GenLab.
IRIS-GenLab is a generative AI Application that leverages the functionality of Flask web framework, SQLALchemy ORM, and InterSystems IRIS to demonstrate Machine Learning, LLM, NLP, Generative AI API, Google AI LLM, Flan-T5-XXL model, Flask Login and OpenAI ChatGPT use cases.
For several years now Visual Studio Code has supported the notebook coding paradigm with a maturing UX and an API that is enabling a notebook extensions ecosystem to grow. One of the best-known notebook platforms is Jupyter Notebooks. A Microsoft team publishes an extension that allows VS Code to handle .ipynb notebook files. These can either work against a local Python environment or connect to a Jupyter Server, which typically hosts remote Python environments with beefier resources.
As an AI language model, ChatGPT is capable of performing a variety of tasks like language translation, writing songs, answering research questions, and even generating computer code. With its impressive abilities, ChatGPT has quickly become a popular tool for various applications, from chatbots to content creation.
But despite its advanced capabilities, ChatGPT is not able to access your personal data. So in this article, I will demonstrate below steps to build custom ChatGPT AI by using LangChain Framework:
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.
Is this a known problem? Should I try another version? Maybe have I just to sit down in a corner and cry like a baby?
Hi Community,
We invite you to join our next Developer Meetup in Boston: What happens next? Demos of the Latest Predictive Analytics technology.
Date: Monday, June 26, 2023 at 5:30 PM - 7:30 PM
Location: Venture Café Cambridge
>> RSVP here <<
On this GitHub you can find all the information on how to use a HuggingFace machine learning / AI model on the IRIS Framework using python.
Usage of Machine Learning models in IRIS using Python; For text-to-text, text-to-image or image-to-image models.
Here, models as example :
Many factors affect a person's quality of life, and one of the most important is sleep. The quality of our sleep determines our ability to function during the day and affects our mental and physical health. Good quality sleep is critical to our overall health and well-being. Therefore, by analyzing indicators preceding sleep, we can determine the quality of our sleep. This is precisely the functionality of the Sheep's Galaxy application.