Jacob Jedryszek joins Scott Hanselman to talk about about using Cognitive Services with Azure Search with your mobile and web apps. Skip hiring search experts who know what an inverted index is.

Don’t worry about distributed systems expertise to scale your service to handle large amount of data.

And forget about setting up, owning and managing the infrastructure. Let Azure Search do it all for you!

In this episode, learn how the Anomaly Detection service comes to your on-premises systems via containers.

By deploying the same API service close to your data in containers, now you don’t have to worry about situations when you have to keep the data on-premises to follow regulation, or to deal with network latency, or just want to reuse the same application powered-by Anomaly Detector across both the cloud and on-premise.

In this episode of the AI Show, get a look at a simple way to detect anomalies that can occur in your data.

Knowing when something goes off the rails is incredibly important and now easily done with a simple API call.

Azure Anomaly Detector Related Links

One of the best tools Microsoft currently has in its AI toolkit is the QnA Maker. It uses NLP to mine one or more source documents and expose the contents as a chatbot. It does a great job of answering, but a newly added feature (Multi-Trun) mimics a crucial ability that a real human adds: the ability to clarify, ask for more information, or do anything more than a one-off question-response type of conversation.

In this article, Matt Wade examines this feature and how to exploit it to make your QnA bots even smarter.

But that all changed with the recent introduction of QnA Maker multi-turn conversations. With multi-turn, the experience with your QnA KB is much more fluid and significantly more natural. Let’s see how.

To say that there’s been a lot of buzz around AI lately would be an understatement and incredibly comedic considering this site is called “Frank’s World of Data Science & AI.” What’s been interesting to see is the evolution of MLaaS, or Machine Learning as a Service, platforms where very little knowledge of computational models are needed to create smarter applications.

Check out this video from GrowthTribe to see why this is a big deal and will impact your career in AI and Data Science.

In this video, learn how to apply AI to understand your business documents by deploying a cognitive search solution on your data, including customer testimonies and demos.

Cognitive search allows you to apply AI (Cognitive Skills) to your data to extract entities and relationships from your unstructured documents, turning them into your private knowledge store. The video also introduces the new Knowledge Store that is now part of Cognitive Search, and explore new features and capabilities (complex type, storage-optimized SKU, etc.).

Chevron’s Canada Business Unit manually mined critical data from drilling and completion reports; a laborious, time-consuming and error-prone process.

The company is now using Microsoft Form Recognizer (a new Microsoft cognitive service) together with UiPath’s robotic process automation platform to automate the extraction of data and move it into back-end systems for analysis. Subject matter experts will have more time to focus on higher-value activities and information will flow more rapidly, accelerating operational control and enabling the company to analyze its business with greater speed, accuracy, and depth.

Here’s an interesting story about data analytics, specifically NLP, and data visualization can breathe new life into classic works of literature.

Phil Harvey, a Cloud Solution Architect at Microsoft in the UK, used the company’s Text Analytics API on 19 of The Bard’s plays. The API, which is available to anyone as part of Microsoft’s Azure Cognitive Services, can be used to identify sentiment and topics in text, as well as pick out key phrases and entities. This API is one of several Natural Language Processing (NLP) tools available on Azure.

As an added bonus, I think there should be an AMC series set in Elizabethan times mirroring the events of Breaking Bad.