Keywords:  IRIS, IntegratedML, Machine Learning, Covid-19, Kaggle 

Continued from the previous Part I ... In part I, we walked through traditional ML approaches on this Covid-19 dataset on Kaggle. 

In this Part II, let's run the same data & task, in its simplest possible form, through IRIS integratedML which  is a nice & sleek SQL interface for backend AutoML options. It uses the same environment. 

IntegratedML Approach?

How to load data into IRIS

ML Toolkit for InterSystems IRIS, besides Python/R/Julia, allows orchestrating cloud-based advanced analytics services, such as Microsoft Azure Data Factory and Machine Learning:

IRIS is an excellent option for machine learning projects with massive data operation scenarios, because the following reasons:

Hi Developers,

The new video from Global Summit 2019 is available on InterSystems Developers YouTube:

⏯ Introducing Analytic Workflows

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.

Source

So Machine Learning Models are not equal Common Applications?

Hi Community!

We're pleased to invite you to the Online Meetup with the Winners of the InterSystems IRIS AI Programming Contest!

Date & Time: Friday, July 24, 2020 – 11:00 EDT

What awaits you at this virtual Meetup? 

• Our winners' bios.
• Short demos on their applications.
• A short interview with all the winners about the past contest. Plans for the next contests.

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:

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: 

⏯ Monitoring your ML model with IntegratedML

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

Exploring Data

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.

Posts Table ( Provided by Intersystems Team )

Tags Table ( Provided by Intersystems Team )

Hi Community,

Please welcome the new video, specially recorded by @Renato Banzai for the InterSystems IRIS AI Programming Contest: 

⏯ IRIS ML Suite Demo

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! :)

Content

Hey Developers,

New "Coding Talk" video was specially recorded by @Yuri Marx for the InterSystems IRIS AI Programming Contest: 

⏯ SAPPHIRE - AutoML UI to InterSystems IntegratedML

Hi guys,

I released the Sapphire - Auto ML UI to IntegratedML in first version. This week we will release more features. At moment you can create your models.

New features to the next 3 days: model training, csv import, model validate and model performance report.

Enjoy!

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!

Welcome the new video from Global Summit 2019 on InterSystems Developers YouTube:

⏯ Reducing Readmissions with Machine Learning

Hi everyone. 
We are a team of company  "Constructor" and we develop cutting edge cartographic systems. Recently the amount of image data skyrocketed so we want to give our users the ability to tie images to places automatically. For that, we want to use AI/ML technologies and we have a cool task for you.

https://cloud.mail.ru/public/pHbC/4r7Z58m6f/

Hi Developers!

Here in Developers Community, we have posts, which are categorized by tags. Tags - are specific topics, which relate to InterSystems products, InterSystems services, or any concept related to software development, deployment, or maintenance etc. 

Tag is a helpful thing because it gives the option to follow/subscribe to the tag, filter the search by the tag,  understand how popular or not unpopular the topic and more.

And we have a problem!

Actually two problems. The tags for the post are selected by the author of the post, and we have the following issues: the author chooses wrong tags for a post, and the post lacks proper tags.

And we think this problem could be solved with AI/ML approach and so we suggest you solve it during the InterSystems IRIS AI Contest.

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: 

⏯ IntegratedML-Template Demo

Hi Community!

Enjoy watching the new video on InterSystems Developers YouTube and learn more about IntegratedML feature:

⏯ IntegratedML: Predicting Readmissions

The Intersystems IRIS is a great platform to develop, run and consume Data Science services. IRIS can ingest data from any type, format, protocol and time using adapters. These datasets can be prepared with BPL, DTL and Object Script and stored as SQL or NoSQL data. Finally, it can be consumed by open ML algorithms inside IRIS and visualized in the IRIS dashboards. See more in:   https://docs.intersystems.com/irislatest/csp/docbook/Doc.View.cls?KEY=PAGE_data_science.

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:

• 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.

Learn more in IntegratedML Resource Guide.

You can use with IntegratedML template.

2. Python Gateway usage - 1 expert vote point

Python Gateway is an addon to InterSystems IRIS which gives you the way to use Python in InterSystems IRIS environment:

• Execute arbitrary Python code.
• Seamlessly transfer data from InterSystems IRIS into Python.
• Build intelligent Interoperability business processes with Python Interoperability Adapter.
• Save, examine, modify and restore Python context from InterSystems IRIS.

Learn more about Python Gateway.

You can use the Python Gateway template, which includes IntegratedML too.

3. Docker container - 1 expert vote point

The application gets a 'Docker container' bonus if it uses InterSystems IRIS  running in a docker container. 

Both templates, IntegratedML template and  Python Gateway template use docker so you can collect this bonus if you build your solution using these templates.

Or you can use any other Docker-based templates, published on Open Exchange.

Feel free to ask any questions about using the listed technologies.

Good luck in the competition!

Keywords:  PyODBC, unixODBC, IRIS, IntegratedML, Jupyter Notebook, Python 3

Purpose

A few months ago I touched on a brief note on "Python JDBC connection into IRIS", and since then I referred to it more frequently than my own scratchpad hidden deep in my PC. Hence, here comes up another 5-minute note on how to make "Python ODBC connection into IRIS".

ODBC and PyODBC seem pretty easy to set up in a Windows client, yet every time I stumbled a bit somewhere on setting up an unixODBC and PyODBC client in a Linux/Unix-style server.

Creating a Chatbot with IRIS and Python

In this article I'm going to show how to integrate the InterSystems IRIS Database with Python to serve a Machine Learning Model of Natural Language Processing (NLP).

Why Python?

With a large adoption and use in the world, Python have a great community and a lot of accelerators | libraries to deploy any kind of application. If you are curious (https://www.python.org/about/apps/).

Iris Globals

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: 

⏯ What is Machine Learning?

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.