Are you using the most appropriate machine learning approach for your use case?
Some machine learning tasks can be completed in real-time, while others require batch processing. This talk will compare and contrast the pros and cons of both approaches, so that you can assess the differences between batch and real-time inference. You will also learn how to do real-time ML using the new Azure ML Endpoints, going from deploying a simple ML model to iterating the changes you need to make in order to get a production-ready service.
By the end of this talk, you will be able to determine whether your projects need batch or real-time ML, and know how to deploy a real-time machine learning model using Azure ML Endpoints.
By day, Vlad works at Strongbytes as Head of AI, and by night he's building NRGI.ai, an upcoming B2B energy marketplace powered by a proprietary AI forecasting engine.The rest of the time he's a Microsoft Most Valuable Professional on AI, plays the ukulele with a vengeance, and blogs about life, the universe and software development at vladiliescu.net...