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#Machine Learning

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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.

This is the third post of a series explaining how to create an end-to-end Machine Learning system.

Training a Machine Learning Model

When you work with machine learning is common to hear this work: training. Do you what training mean in a ML Pipeline?
Training could mean all the development process of a machine learning model OR the specific point in all development process
that uses training data and results in a machine learning model.

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Announcement
· Sep 12, 2019
Python Gateway 0.8 release

I'm happy to announce the latest Python Gateway release.

This is not an InterSystems product, it is community supported open source project.

Download new release from GitHub.

Now for the new features.

Fast transfer. Pass globals, classes and tables from InterSystems IRIS to Python with ease and speed (10x faster than old QueryExecute). Documentation.

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Hey Community,

We're pleased to invite you to the InterSystems AI+ML Summit 2021, which will be held virtually from January 25 to February 4! Join us for a two-week event that ranges from thought leadership to technical sessions and even 1:1 “Ask the Expert” sessions.

The sessions will be in both German and English. And this summit is free to attend!

See details below:

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In this article you will have access to the curated base of articles from the InterSystems Developer Community of the most relevant topics to learning InterSystems IRIS. Find top published articles ranked by Machine Learning, Embedded Python, JSON, API and REST Applications, Manage and Configure InterSystems Environments, Docker and Cloud, VSCode, SQL, Analytics/BI, Globals, Security, DevOps, Interoperability, Native API. Learn and Enjoy!

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Announcement
· Aug 30, 2018
Machine Learning 101 Presentation

View Machine Learning 101 recording at: https://videos.intersystems.com/detail/video/5827774460001/machine-learning-101?autoStart=true&q=machine%20learning.

In addition to our webinar on machine learning (https://community.intersystems.com/post/rescheduled-webinar-its-machine-learning-not-rocket-science-july-31-1100-am-edt), we are pleased to announce a basic introduction to machine learning presentation that provides an overview of the basic algorithms by @Don Woodlock, InterSystems VP of HealthShare Platforms.

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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.

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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.

What if your InterSystems IRIS environments, whether local on your workstation or remote in your organization / cloud, could operate as Jupyter Servers? And not only for Embedded Python but also for ObjectScript and SQL

"If we build it, will they come?"

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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.

1. iris-huggingface

Usage of Machine Learning models in IRIS using Python; For text-to-text, text-to-image or image-to-image models.

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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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Hi Everyone!

Very soon, almost every product and application will include artificial intelligence (AI).

On the afternoon of Wednesday, October 3, at the Global Summit 2018 in San Antonio we’re pulling together experts from InterSystems and from the front lines of the AI industry to discuss the current and future state-of-the-art for AI solutions.

Learn more about our Post-Summit Symposium: Artificial Intelligence and Machine Learning.

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Hi Community!

We are pleased to invite all the developers to the upcoming InterSystems Analytics Contest Kick-off Webinar! The topic of this webinar is dedicated to the Analytics contest.

On this webinar, we’ll demo the iris-analytics-template and answer the questions on how to develop, build, and deploy Analytics applications using InterSystems IRIS.

Date & Time: Monday, December 7 — 12:00 PM EDT

Speakers:
🗣 @Carmen Logue, InterSystems Product Manager - Analytics and AI
🗣 @Evgeny Shvarov, InterSystems Developer Ecosystem Manager

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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
[This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]

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The last time that I created a playground for experimenting with machine learning using Apache Spark and an InterSystems data platform, see Machine Learning with Spark and Caché, I installed and configured everything directly on my laptop: Caché, Python, Apache Spark, Java, some Hadoop libraries, to name a few. It required some effort, but eventually it worked.

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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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Hey Developers,

This week is a voting week for the InterSystems Analytics Contest! So, it's time to give your vote to the best solutions built with InterSystems IRIS.

🔥 You decide: VOTING IS HERE 🔥

How to vote?

Please meet the new voting engine and algorithm for the Experts and Community nomination:

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Hi Community,

We're pleased to invite you to the online meetup with the winners of the InterSystems Analytics Contest!

Date & Time: Monday, January 4, 2021 – 10:00 EDT

What awaits you at this virtual Meetup?

  • Our winners' bios.
  • Short demos on their applications.
  • An open discussion about technologies being used, bonuses, questions. Plans for the next contests.

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Hi all.

I want to insert my dataframe into InterSystems IRIS. So, I tried to do this:

df = spark.read.load("/home/imported-openssh-key/zeppelin-0.8.0-bin-all/bin/resultData3/DF.json", format="json")
df.write.format("com.intersystems.spark").\
option("url", "IRIS://localhost:51773/DEDUPL").\
option("user", "********").option("password", "********").\
option("dbtable", "try.test1").save()

And got this error:

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