ML.NET is an open source, cross platform, machine learning framework for .NET developers. In this talk, you'll learn about the framework, its main components for building custom machine learning models and how to deploy such models into production.
IMPORTANT: Your RSVP with full name is required to add your name to the building security guest list.
6:00PM - NETWORKING: Doors open, head to the room identified when you check in. Pizza will be catered and should arrive around 6PM. Take the opportunity to grab a slice and mingle with your fellow community developers.
6:30PM - INTRODUCTION: Housekeeping, open mic and other community announcements & request.
6:45PM - MAIN PRESENTATION: ML.NET is an open source, cross platform, machine learning framework for .NET developers that was released at Build 2018. Throughout this past year, the technology has been strongly evolving with monthly point releases that further solidify the API and cover more machine learning tasks. In addition to helping developers build custom models, it integrates with other frameworks such as TensorFlow and ONNX further expanding its interoperability and use cases. In this talk, you'll learn about the framework, its main components for building custom machine learning models and how to deploy such models into production.
Luis Quintanilla (https://twitter.com/ljquintanilla) is a Content Developer at Microsoft working primarily on ML.NET helping create resources that make it easier for .NET developers to get started in their AI and machine learning journey. In a prior life as an AI consultant, he helped companies envision how they could transform their businesses with AI and ML solutions. When not at work, he's usually tinkering with different tools/technologies, applying them in different scenarios and blogging about it (http://luisquintanilla.me/).