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.
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Please welcome the new video on InterSystems Developers YouTube:
Hi Community,
We're pleased to invite all the developers to the upcoming InterSystems AI Contest Kick-Off Webinar! The topic of this webinar is dedicated to the InterSystems AI programming contest.
During the webinar, we will demo how to load data into IRIS, how to deal with it using ODBC/JDBC and REST, and how to use special AI/ML features of IRIS: IntegratedML, DataRobot, R Gateway, Embedded Python, PMML.
Date & Time: Monday, June 28 — 11:00 AM EDT
Speakers:
🗣 @Aleksandar Kovacevic, InterSystems Sales Engineer
🗣 @Théophile Thierry, InterSystems Intern
🗣 @Bob Kuszewski, Product Manager - Developer Experience, InterSystems
🗣 @Evgeny Shvarov, InterSystems Developer Ecosystem Manager
Hi!
I'd like to know how to get feature importance after creating and training a model, using IntegratedML with AutoML provider?
Thanks!
When we have to predict the value of a categorical (or discrete) outcome we use logistic regression. I believe we use linear regression to also predict the value of an outcome given the input values.
Then, what is the difference between the two methodologies?
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Please welcome the new video on InterSystems Developers YouTube:
What is Distributed Artificial Intelligence (DAI)?
Attempts to find a “bullet-proof” definition have not produced result: it seems like the term is slightly “ahead of time”. Still, we can analyze semantically the term itself – deriving that distributed artificial intelligence is the same AI (see our effort to suggest an “applied” definition) though partitioned across several computers that are not clustered together (neither data-wise, nor via applications, not by providing access to particular computers in principle). I.e., ideally, distributed artificial intelligence should be arranged in such a way that none of the computers participating in that “distribution” have direct access to data nor applications of another computer: the only alternative becomes transmission of data samples and executable scripts via “transparent” messaging. Any deviations from that ideal should lead to an advent of “partially distributed artificial intelligence” – an example being distributed data with a central application server. Or its inverse. One way or the other, we obtain as a result a set of “federated” models (i.e., either models trained each on their own data sources, or each trained by their own algorithms, or “both at once”).
Keyword: Pandas DataFrame, IRIS, Python, JDBC
Pandas DataFrame is popular tool for EDA (Exploratory Data Analysis). In ML tasks, the first thing we usually perform is to understand the data a bit more. Last week I was trying this Covid19 dataset in Kaggle. Basically the data is a spreadsheet of 1925 encounter rows with 231 columns, and the task is simply to predict whether a patient (linked to 1 or more encounter records) would be admitted to ICU. So it's a normal classification task, and we would as usual use padas.DataFrame to take a quick look first.
Hi Developers,
Please welcome the new video on InterSystems Developers YouTube:
Hi Community,
Enjoy watching the new session recording from the InterSystems AI+ML Summit 2021:
Hey Developers,
Please welcome the new session recording from the InterSystems AI+ML Summit 2021:
Hi Developers!
Please welcome the new video on InterSystems Developers YouTube:
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:
Hi Community,
As you may know, this year we're holding InterSystems AI+ML Summit 2021 virtually from January 25 to February 4. All sessions, both in German and English, will be free to attend.
Let's find out more about the exciting sessions that await us and book a virtual seat today!
Check the agenda below:
Artificial intelligence has solved countless human challenges – and medical coding might be next.As organizations prepare for ICD-11, medical coding is about to become more complicated. Healthcare organizations in the United States already manage 140,000+ codes in ICD-10. With ICD-11, that number will rise.Some propose artificial intelligence as a solution. AI could aid computer-based medical coding systems, identifying errors, enhancing patient care, and optimizing revenue cycles, among other benefits.Today, we’re highlighting some of the ways in which artificial intelligence could change
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?
Hey Developers,
The InterSystems Analytics Contest is over. Thank you all for participating in our exciting coding marathon!
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 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:
Hey Developers!
We're pleased to invite you all to the next competition of creating open-source solutions using InterSystems IRIS! Please join:
🏆 InterSystems Analytics Contest 🏆
Duration: December 7 - 27, 2020
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
GA releases are now published for the 2020.3 version of InterSystems IRIS, IRIS for Health, with IntegratedML!
Keywords: Python, JDBC, SQL, IRIS, Jupyter Notebook, Pandas, Numpy, and Machine Learning
This is another 5-minute simple note on invoking the IRIS JDBC driver via Python 3 within i.e. a Jupyter Notebook, to read from and write data into an IRIS database instance via SQL syntax, for demo purpose.
Hi Community,
See how IntegratedML can leverage DataRobot — a best-in-class, third-party machine learning platform — to make predictions on a set of data:
Hi Community,
See how IntegratedML in InterSystems IRIS can be used to make machine learning predictions directly from SQL commands:
Hey Developers,
See how InterSystems IRIS Adaptive Analytics can be used to aggregate and query billions of records from a virtual cube, applying machine learning and analytics to that data.
IRIS is an excellent option for machine learning projects with massive data operation scenarios, because the following reasons:
Keywords: COVID-19, Medical Imaging, Deep Learning, PACS Viewer, and HealthShare.
We are all gripped by this unprecedented Covid-19 pandemic. While supporting our customers in battlefields by any means, we also observed various fighting fronts against Covid-19 by leveraging today's AI powers.
Hi Community!
Enjoy watching the new video on InterSystems Developers YouTube:
Keywords: IRIS, IntegratedML, Flask, FastAPI, Tensorflow Serving, HAProxy, Docker, Covid-19
Keywords: IRIS, IntegratedML, Machine Learning, Covid-19, Kaggle
Recently I noticed a Kaggle dataset for the prediction of whether a Covid-19 patient will be admitted to ICU. It is a spreadsheet of 1925 encounter records of 231 columns of vital signs and observations, with the last column of "ICU" being 1 for Yes or 0 for No. The task is to predict whether a patient will be admitted to ICU based on known data.
NLP stands for Natural Language Processing which is a field of Artificial Intelligence with a lot of complexity and techniques to in short words "understand what are you talking about".
FHIR stands for Fast Healthcare Interoperability Resources and is a standard to data structures for healthcare. There are some good articles here explainig better how FHIR interact with Intersystems IRIS.