Hi Developers!
The InterSystems IRIS AI Contest is over. Thank you all for participating in our IRIS AI Competition!
And now it's time to announce the winners!
A storm of applause goes to these developers and their applications:
InterSystems IntegratedML is an all-SQL machine learning (ML) module for InterSystems IRIS or IRIS for Health that:
- 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.
Please find more information including videos and infographics at the IntegratedML Resource Guide.
Hi Developers!
The InterSystems IRIS AI Contest is over. Thank you all for participating in our IRIS AI Competition!
And now it's time to announce the winners!
A storm of applause goes to these developers and their applications:
Sapphire has CSV import, create and train IntegratedML model and I will create more features. See the pool. Check sapphire in https://openexchange.intersystems.com/package/SAPPHIRE
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.
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.
Hi Developers,
Please welcome the new video, specially recorded by @José Pereira for the InterSystems IRIS AI Programming Contest:
This is the second post of a series explaining how to create an end-to-end Machine Learning system.
The InterSystems 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.
Hi Community,
Please welcome the new video, specially recorded by @Renato Banzai for the InterSystems IRIS AI Programming Contest:
Following up the previous part, it's time to take advantages for IntegratedML VALIDATION MODEL statement, to provide information in order to monitor your ML models. You can watch it in action here
The code presented here was derived from examples provided by either InterSystems IntegragedML Template or IRIS documentation, my contribution was mainly mashing up such codes. It's a simple example intended to be a start for discussions and future works.
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.
I simulated a simple performance issue scenario in an Open Exchange technology example application - iris-integratedml-monitor-example, which is competing in the InterSystems IRIS AI Contest. Please, after read this article, you can check it out and, if you like it, vote for me! :)
Hey Developers,
New "Coding Talk" video was specially recorded by @Yuri Marx for the InterSystems IRIS AI Programming Contest:
Hey Developers!
Join our next competition in creating open-source solutions using InterSystems IRIS Data Platform! Please welcome:
➡️ InterSystems IRIS AI Programming Contest ⬅️
Duration: June 29 – July 19, 2020.
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
Hi Developers,
Please welcome the new video, specially recorded by @Zhong Li for the InterSystems IRIS AI Programming Contest:
Hi Community!
Enjoy watching the new video on InterSystems Developers YouTube and learn more about IntegratedML feature:
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!
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:
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.
The build number for these releases is: 2020.3.0AA.331.0
Full product installation kits, container images, and evaluation license keys are available via the WRC's preview download site.
Community Edition containers can also be pulled from the Docker store using the following commands:
Hi Developers,
New to machine learning? Watch this video on InterSystems Developers YouTube to understand the basic concepts of machine learning and how it provides value in applications around the world today:
Hey Developers,
We're pleased to invite you to the "Best practices of in-platform AI/ML" webinar by InterSystems on April 28th at 11:00 EST/17:00 CET.
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!
Hi Community!
Enjoy watching the new video on InterSystems Developers YouTube and learn about IntegratedML feature:
Greetings Developer Community!
InterSystems IntegratedML (formerly known as QuickML) is ready for external beta, and is looking for some users to kick the tires!
IntegratedML is an all-SQL machine learning (ML) feature in IRIS that:
• Gives users the ability to create, train and deploy powerful models from simple SQL syntax
• Wraps "best of breed" open source and proprietary ML and "automl" frameworks such as TensorFlow, XGBoost, H2O-3, and DataRobot
• Focuses on ease of deployment, so you can add predictions to your application with a single SQL function call
You may have seen earlier this week that we launched a brand-new learning podcast called Data Points! There 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!
InterSystems IRIS ML Toolkit adds the power of InterSystems IntegratedMLto 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.