Azure

Recently, I worked on a project where I leveraged Azure Service Bus Filters to optimize message handling. Below is a detailed summary of what I learned and how these filters can be effectively used. What are Azure Service Bus Filters? Azure Service Bus Topics provide a robust way to publish messages to multiple subscribers, following a pub/sub model. In this model, a topic acts as a queue where messages are sent, and subscriptions to that topic allow selective filtering and processing of messages. Filters and actions are key features that enable precise control over which messages subscribers receive and how they are processed. ...

I started to study for AI102 Certification. Preparing for the AI-102 certification is an excellent way to deepen understanding of Azure AI services. Here’s a breakdown of the key services that is related with exam: Azure AI Services Overview Azure Cognitive Services – These are pre-built AI models that allow developers to integrate AI capabilities into applications. They include: Vision (e.g., Computer Vision, Face API) Speech (e.g., Speech-to-Text, Text-to-Speech, Translator) Language (e.g., Text Analytics, Language Understanding) Decision (e.g., Personalizer) Search (e.g., Azure AI Search) Azure Machine Learning – A comprehensive cloud-based service that helps in building, training, and deploying ML models efficiently. Key components include: ...

Now studying more on Azure AI services, below is an in-depth look at how to map specific business requirements and use cases to the various Azure AI services. While the ultimate choice always depends on end-to-end needs—ranging from time-to-market and customization to scalability and regulatory constraints—here are some guiding principles: 1. Azure Cognitive Services When It Fits: Rapid Integration & Out-of-the-Box Capabilities: If your business needs to add AI capabilities quickly without developing and training custom models from scratch, Cognitive Services are ideal. They provide pre-built APIs for vision, speech, language, decision support, and more. Example use cases: ...

Let’s take a deeper dive into how you might choose between Azure Cognitive Services, Azure Machine Learning, and Azure Bot Services in real-world business scenarios. 1. Azure Cognitive Services When to Use It Quick Integration & Out-of-the-Box Capabilities: If your business needs an immediate boost by incorporating AI into existing applications without building models from scratch, Cognitive Services fit the bill perfectly. They offer pre-trained APIs for vision (image recognition, OCR), speech (speech-to-text, text-to-speech), language (sentiment analysis, translation), and decision making (personalizers, anomaly detectors). ...

Below is a detailed, step‐by‐step integration guide written entirely in C#. In this scenario, a retail chatbot uses: Azure Cognitive Services (LUIS): to parse customer messages and extract intents and entities. Azure Machine Learning: to call a custom recommendation model that produces personalized product suggestions. Azure Bot Services:—using the Bot Builder SDK for .NET—to drive a conversational interface that ties it all together. Step 1: Define Business Requirements & Architecture Business Use Case: A retail business wants a conversational assistant on its website. When a customer sends a query (e.g., “I’m looking for summer dresses”), the solution should: ...