It's true! QuinielaML has incorporated the most important leagues in Europe (and Brazil) into its prediction service, so, dear members of the Developer Community, wherever you are from, you will be able to have the predictions of your favorite leagues at your disposal.

From the predictions screen you will have access to each of the new leagues included, being able to record the matches for each journey:

Hey Developers,

Enjoy watching the new video on InterSystems Developers YouTube:

⏯ InterSystems Cloud Services - InterSystems IRIS SQL & IntegratedML @ Global Summit 2023

https://www.youtube.com/embed/jjYnVsF9xeI
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We continue with the series of articles related to the QuinielaML application. In this article we are going to cover how to prepare the raw data that we have captured using the Embedded Python functionality.

Welcome everybody!

Taking advantage of the Quiniela ML application and as we indicated in the previous article, we are going to explain how we can perform a JWT authentication between our frontend developed in Angular and our backend developed in InterSystems IRIS.

I remind you of the architecture of our QuinielaML project:

Hi Developers,

Watch this video to learn about new features of IntegratedML, such as support for larger datasets and new syntax for time series forecasting:

⏯ IntegratedML: New & Next @ Global Summit 2023

https://www.youtube.com/embed/uCyjFozKad8
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A simple data analysis example created in IntegratedML and Dashboard

Based on InterSystems' Integrated ML technology and Dashboard, automatically generate relevant predictions and BI pages based on uploaded CSV files. The front and back ends are completed in Vue and Iris, allowing users to generate their desired data prediction and analysis pages with simple operations and make decisions based on them.

# ZPM installation

zpm:USER>install IntegratedMLandDashboardSample

# Process Deployment

InterSystems IRIS Cloud SQL is a fully managed cloud service that brings the power of InterSystems IRIS relational database capabilities used by thousands of enterprise customers to a broad audience of application developers and data professionals. InterSystems IRIS Cloud IntegratedML is an option to this database-as-a-service that offers easy access to powerful Automated Machine Learning capabilities in a SQL-native form, through a set of simple SQL commands that can easily be embedded in application code to augment them with ML models that run close to the data.

Today, we announce the Developer Access Program for these two offerings. Application developers can now self-register for the service, create deployments and start building composable applications and smart data services, with all provisioning, configuration and administration taken care of by the service.

Hi colleagues!

InterSystems Grand Prix 2023 unites all the key features of InterSystems IRIS Data Platform!

Thus we invite you to use the following features and collect additional technical bonuses that will help you to win the prize!

Here we go!

• LLM AI or LangChain usage: Chat GPT, Bard and others - 6
• InterSystems FHIR SQL Builder- 5
• InterSystems FHIR - 3
• IntegratedML - 4
• Native API - 3
• Embedded Python - 4
• Interoperability - 3
• Production EXtension(PEX) - 2
• Adaptive Analytics (AtScale) Cubes usage - 3
• Tableau, PowerBI, Logi usage - 3
• InterSystems IRIS BI - 3
• Columnar Index Usage - 1
• Docker container usage - 2
• ZPM Package deployment - 2
• Online Demo - 2
• Unit Testing - 2
• Implement InterSystems Community Idea - 4
• First Article on Developer Community - 2
• Second Article On DC - 1
• Code Quality pass - 1
• First Time Contribution - 3
• Video on YouTube - 3

In recent years, artificial intelligence technologies for text generation have developed significantly. For example, text generation models based on neural networks can produce texts that are almost indistinguishable from texts written by humans.
ChatGPT is one such service. It is a huge neural network trained on a large number of texts, which can generate texts on various topics and be matched to a given context.

Hi Developers,

IntegratedML is a feature helps us and our teams easily implement machine learning (ML) without dedicated ML experts and data scientists. If you do not need particularly complex ML function, integratedML is a good choice and convenient that only requires executing 3 SQL queries to build predictive models directly from InterSystems IRIS to ML engine.

It is very interesting to compare different BI technologies. It is curious to me what the differences are in functionality, development tools, speed and usability.

Kidney Disease can be discovered from some parameters well known to the medical community. In this way, in order to help the medical community and computerized systems, especially AI, the scientist Akshay Singh published a very useful dataset for training ML algorithms in the detection/prediction of kidney disease. This publication can be found on the largest and best known data repository for ML, Kaggle at https://www.kaggle.com/datasets/akshayksingh/kidney-disease-dataset.

Is it possible train an IntegratedML model on docker build or docker up?

Hi community,

Prediction is a critical to the Maternal healthcare. The Health Dataset Application (https://openexchange.intersystems.com/package/Health-Dataset) has 10 real health datasets to predict the most important diseases and health problems, including Maternal Risk.

This article detail the steps to predict Maternal Risk using the InterSystems IRIS IntegratedML. This is a technology of InterSystems to do predictions using SQL Commnands! Great!

Follow these steps: