Developer Support

Advocacy and Innovation

How to enhance your chatbot so it can retrieve data from multiple data sources & orchestrate its own plan with C# Semantic Kernel, planner & Azure OpenAI – part 4 (local development & deployment details)

In this multi-part series, Jordan Bean shares how to enhance a chatbot to retrieve data from multiple data sources and orchestrate plans with C# Semantic Kernel, planner, and Azure Open AI. In the previous post, I detailed how the demo app runs. In this post, let’s talk about some of the techniques & technologies I used to make...

How to enhance your chatbot so it can retrieve data from multiple data sources & orchestrate its own plan with C# Semantic Kernel, planner & Azure OpenAI – part 3 (demo app)

In this multi-part series, Jordan Bean shares how to enhance a chatbot to retrieve data from multiple data sources and orchestrate plans with C# Semantic Kernel, planner, and Azure Open AI. In the previous post, we talked about the implementation details of how the demo app works & how to set up Semantic Kernel, with the  and...

How to enhance your chatbot so it can retrieve data from multiple data sources & orchestrate its own plan with C# Semantic Kernel, planner & Azure OpenAI – part 2 (demo app implementation)

In this multi-part series, Jordan Bean shares how to enhance a chatbot to retrieve data from multiple data sources and orchestrate plans with C# Semantic Kernel, planner, and Azure Open AI. In the previous post, we discussed how the RAG pattern isn’t enough to answer complex user questions. We talked about using Semantic Kernel ...

How to enhance your chatbot so it can retrieve data from multiple data sources & orchestrate its own plan with C# Semantic Kernel, planner & Azure OpenAI – part 1

In this multi-part series, Jordan Bean shares how to enhance a chatbot to retrieve data from multiple data sources and orchestrate plans with C# Semantic Kernel, planner, and Azure Open AI. As discussed in the previous post about Azure OpenAI, using the Retrieval Augmented Generation (RAG) pattern is a simple & effective way to ...

Introduction to Supervised Machine Learning

Machine learning is a very powerful tool for businesses and researchers to create predictions for data problems. However, there are many steps to creating models and not every model is suited for each problem. We have to use a combination of human judgment and computational techniques to create the right model.

Bias in Machine Learning

Machine learning is the scientific study of algorithms and statistical models that result in devices automatically learning and improving from experiences without being explicitly programmed. With so much success integrating machine learning into our everyday lives, the obvious next step is to integrate machine learning into even more systems.

Using Azure Cognitive Services Text Analytics API Version 3 Preview for Sentiment Analysis

In this blog, I will demonstrate how Text Analytics API Version 3 Preview of the Microsoft Azure Cognitive Services can be used to analyze large unstructured data. This analysis aims to understand the sentiments expressed in a solicited public comment process and determines the degree of the positivity or negativity of the comments.

Azure AI does that?

Whether you’re just starting off in tech, building, managing, or deploying apps, gathering and analyzing data, or solving global issues —anyone can benefit from using cloud technology. In this post, we will explore some practical examples where Azure AI is driving innovation.