Articles filed in category 'Machine Learning'

If you’ve been thinking that Artificial Intelligence and Machine Learning are a bit out of your league, think again. Sahil shows that you’re already using and benefiting from it, and you can create it too.

Sahil explores the limitations of Cognitive Services, the potential of Azure Machine Learning, and creating your own AI models.

It’s when you’re working with lots of data that you start looking around for an easier way to keep track of it all. Machine learning and artificial intelligence seem like the obvious answers, and Sahil shows you why.

Sahil Malik’s article demystifies the rise of bots as the next era of human–computer interaction, arguing that bots are simply conversational interfaces built with the Microsoft Bot Framework. He explains core concepts—dialogs, state, channels, and the waterfall pattern—while outlining pragmatic design guidelines (simplicity, usefulness, and non-annoyance), and shows how to develop, test, and deploy bots across platforms (including Microsoft Teams) with practical steps, ...tooling (Bot Framework Emulator, ngrok), and concrete code, culminating in a basic Hello World bot and a Teams-ready example.See More

Your household will never be the same after you get Alexa. Chris shows you how to help her understand your requests by building a small trivia game.

Search is everywhere. But unless you add it to your app, you won’t find it there! Sahil examines the various search tools in the Microsoft ecosystem and shows you how to make the most of them.

Got a sinking feeling that you’re missing something in Artificial Intelligence? This article is only the tip of the iceberg, but Wei-Meng offers you a helping hand into the lifeboat called Microsoft Azure Machine Learning Studio.

When it’s time to wire your house to precipitate your every whim or need, you want to be sure that your robot doesn’t mistake “catsup” for “catnip.” Sahil talks about facial recognition and how it’s connected to speech and understanding.

In this next installment of his exploration into artificial intelligence, Sahil explores Microsoft Cognitive Services’ ability to recognize voices from a thirty-second sample.

Instead of implementing machine learning algorithms manually, Wei-Meng found that someone else had already done the hard part. Come along as he explores a Python tool, called Scikit-learn, and builds a couple of models.

Learning R sets you up for creating machine learning projects. Wei-Meng takes a close look at the language, which can implement a wide variety of statistical techniques, tests, analysis, classification, clustering, and can help you produce publication-quality graphs.

Python has long been the favorite language of open-source developers. Nicola shows Windows and iOS developers how to take advantage of Python’s many qualities using Visual Studio.

Machine Learning doesn’t have to be the big scary monster lurking in the dark. Bri and Cesar show you how Microsoft’s ML.NET lets you design your own models specific to your deployment context and needs even if you’ve never played with ML before.

Sahil Malik’s article explains how Natural Language Understanding with Microsoft LUIS lets developers convert free-form user input into actionable intents and entities, using domain-focused models that can be trained, tested, and refined through iterative utterances and patterns. He illustrates both browser-based and programmatic workflows—creating, training, and publishing LUIS apps via REST APIs, integrating with applications, and securing calls. Through step-by-step e...xamples (creating apps, adding intents/entities, supplying utterances, and consuming results), Malik demonstrates how to automate and scale natural-language capabilities in software, highlighting cognitive services’ power and practical integration considerations.See More

SQL Server 2017 has machine learning services baked right in. If you’ve been wondering how to use it, you’ll be fascinated by what Jeannine’s serves up.