Machine Learning/ AI and Claris FileMaker

Thanks for checking out this collection of examples of machine learning with the Claris platform. This article contains severals videos and a podcast that features machine learning and the Claris platform.

A collection of Ml and AI from iSolutions content over the years

Integrating a Summary and Keyword Extraction model with a FileMaker app

Continuing in a series of articles that look at integrating machine learning into FileMaker apps, this article focuses on Summary and Keyword Extraction models.

Summary extraction is a text analysis technique that automatically extracts the most used and most important words and expressions from a text.

Extraction models use natural language processing (NLP) to break down human language so that it can be understood and analyzed by apps like FileMaker apps.

Summary extraction is useful for businesses because it uses automated AI programs to analyze documents and online conversations that may otherwise take hundreds of employee hours to accomplish.

For those who have access to Linkedin Learning, you may have seen an Summary Extraction example I called “Just The Facts” where I whimsically showed how you can take very long emails that have been sent to you and forward them to an account that will process the long-form text and email you have a short summary using Claris Connect:

I had also explored looking into summary and keyword extraction in the context of FileMaker in Education.

At the very beginning of this next video, I show how to use Claris Connect to extract the transcript from a Zoom lesson, then extract a summary and keyword list form that transcript:

In a brand new video, I demonstrate how to use the SMMRY API to send a block of FileMaker text to the API so the API can summarize the text and send back JSON with the summary and keywords. I use native FileMaker functions to parse out the responded JSON values into FileMaker fields.

Keyword extraction uses machine learning artificial intelligence (AI) with natural language processing (NLP) to break down human language to it can be evaluated in apps like FileMaker apps.

It can be used used to find keywords regular documents, reports, social media reviews, news and more.

In the Part two video, I walk through the steps of integrating a machine learning model API call into your FileMaker apps:

In this video I demonstrate how to use the SMMRY API Machine Learning model to extract keywords from home rental listing reviews.

If you would be interested in an evaluation of your business’ data to see if machine learning can benefit your organization, please reach out to us here at iSolutions and we would be happy to discuss options in the context of your data.

Creating a Sentiment Model and integrating with a FileMaker app

Discussing Core ML and Claris FileMaker

iSolutions discusses Core ML support in FileMaker 19 and other ways to integrate machine learning

Creating a Vision Model using Create ML and Claris FileMaker

FileMaker version 19 introduced native machine learning into the Claris platform, but Cris Ippolite has been integrating ML into FM for over a decade.

Talking Machine Learning on The Context Podcast

The Context Podcast

Doanload Podcast: 6871.mp3

EPISODE DETAILS

Cris Ippolite joins us today to talk Machine Learning in Claris FileMaker

SHOW NOTES

Did you know FileMaker has been featured in sports? Specifically an app built by today’s guest appeared all around that world as one of the best apps in a particular segment. This amazing feat, making predictions about how individual players in the league would do garnered a lot of attention from inside the league and outside. And now Claris has featured the app in a great video highlighting how this app performed so well.

Cris Ippolite from iSolutions joins me today to talk Machine Learning in FileMaker. He’s worked extensively with this idea, first as a hobby and now as part of what he does to use the Claris FileMaker platform to make predictions about all sorts of things. In this episode, Cris and I talk about how Machine learning works, what we can do with it, and its implications. He gives us many examples; I even stumble on some of those, and we discuss how machine learning is used all around us.

Cris also shares the story behind this powerful prediction model he’s built that has been featured in many places.

Machine Learning is a powerful and exciting/scary tool. And Cris is here to highlight the power and the scariness.

Machine Learning and Claris in Education

Various examples of machine learning in the context of education.

Custom News Reading Machine Learning Model

Demonstration of using Machine Learning to look for positive or negative news items

Core ML and Claris FileMaker: User Group Discussion

Cris Also discusses CoreML in this user group demonstration:

Cris Ippolite talking Core ML at a FileMaker User Group

Fun Core ML Vision Model Use Case

Hot Dog / Not Hot Dog as a FileMaker App

Monkey Learn Summary Extraction API Model Example

“Just The Facts” example uses Monkey Learn’s summary extraction model and Claris Connect

Core ML Vision Model Example

Core ML Vision Model example

Cris Ippolite talking Machine Learning on the Context Podcast

Cris Ippolite of iSolutions joined Todd and Jeremy in the Context Podcast to talk about only a few things in the Claris FileMaker 19 platform: the Open Platform release, Execute FileMaker Data API script step, and Core ML. Lots of other features get talked about as well.

The Context Podcast — FileMaker 19: Execute FileMaker Data API, and CoreML with Cris Ippolite

PLAY EPISODE or DOWNLOAD (199 MB)

This episode is brought to you by FMPerception.

Cris Ippolite is our guest. He’s the Founder / Head Coach / Trainer of iSolutions.
Cris has courses on LinkedIn Learning. Check those out to learn more about Claris FileMaker 19.

Things we talked about:
1. Todd’s thoughts on the Open Platform Release.
2. Blog post the Perform FileMaker Data API script step, as it returns records in JSON or metaData.
3. CoreML at Apple.