Last week at its annual Build conference, Microsoft announced ML.NET, an “open source and cross-platform machine learning framework” that runs in .NET Core. I took a look at the getting started samples and realized ML.NET would be a great tool to use in OpenFaas functions. I decided to write a proof-of-concept function based on the ML. »
For the last several months I’ve been working on an enterprise Dynamics CRM project where one of our goals is to minimize the amount of custom code we write by using North52’s Business Process Activities. I had not been exposed to North52 before working on this project, but I have been pleasantly surprised with how much it has allowed our mostly functional resources to achieve without needing technical assistance. »
On Monday, April 11, at 12 p.m. EDT, I will be presenting a webcast at MSDynamicsWorld.com that will show how a custom integration with Microsoft Azure Machine Learning can be used to perform sentiment analysis on any data stored in Dynamics CRM. Custom sentiment analysis integrations can enable a number of interesting processes in Dynamics CRM including: »
Last year I created a proof-of-concept solution that showed how to integrate Dynamics CRM with HP Haven OnDemand (then called HP IDOL OnDemand) to perform sentiment analysis and index records to support “find similar” queries. While I was working through the AzureCon challenge a few weeks ago, I thought it would be an interesting exercise to update my sentiment analysis code to work with the Text Analytics offering from the Microsoft Azure Marketplace. »
In my last post I provided a detailed walkthrough of how to perform sentiment analysis on incoming emails received in Microsoft Dynamics CRM by parsing them with HP IDOL OnDemand’s sentiment analysis API and then storing the calculated sentiment values on the email records. In today’s post, I will show a similar, but slightly more complex integration that enables “find similar” functionality for emails stored in Dynamics CRM. »