Getting practical with ML .NET

4:30 odp. - 5:30 odp. (UTC)

This event is a part of "Getting Practical with ML.NET" series Series Description In the near future, every application on every platform will incorporate some form of machine learning capabilities, empowering the application itself and making it smarter. In this series, you'll learn how the ML.NET framework has been designed to democratise the art of machine learning, converting it into a technology available to all developers around the globe. You'll also see practical examples of how you can implement a solution in the ML.NET framework, using a real-world scenario and 2 different approaches: low code and code-heavy. Episode 1: Getting started with ML.NET What is the session about? The session is aimed at introducing you to what is ML.NET and how it is different from the many different frameworks for machine learning there are. We will also be setting up the environment to be ready to develop a new project in this framework! Who is it aimed at? This session is for students, early career and professionals who are interested in setting themselves up to build smart apps using ML.NET Why should you attend? If you think of yourself as a developer or an aspiring software engineer, you might see machine learning as a separate art, practiced by an elite of data scientists and statisticians, and you might be uncertain about how it fits into application development. Attend this session if you wish to find an answer to your doubts. Speaker bio's Carlotta Castelluccio, Cloud Advocate Microsoft Carlotta Castelluccio is a Cloud Advocate at Microsoft, focused on Data Analytics and Data Science. As a member of the Developer Relationships Academic team, she works on skilling and engaging educational communities to create and grow with Azure Cloud, by contributing to technical learning content and supporting students and educators in their learning journey with Microsoft technologies. Before joining the Cloud Advocacy team, she worked as an Azure and AI (ARTIFICIAL INTELLIGENCE) consultant in Microsoft Industry Solutions team. Connect with Carlotta https://www.linkedin.com/in/carlotta-castelluccio/ https://twitter.com/carlottacaste Liam Hampton, Regional Cloud Advocate, Microsoft Liam is a Regional Cloud Advocate at Microsoft. He is an IoT hobbyist, a podcast co-host and a Software Engineer with multiple Professional Cloud Certifications. He is passionate about cloud computing, clean code and creating simple and concise content for others. When he is not writing code or presenting, you'll either find him searching for the next best eatery in London, studying different cultures or at the airport jetting of to explore the next city on his TODO list. Connect with Liam Twitter: https://twitter.com/liamchampton Linkedin: https://www.linkedin.com/in/liam-conroy-hampton/

4:30 odp. - 5:30 odp. (UTC)

This event is a part of "Getting Practical with ML.NET" series Series Description In the near future, every application on every platform will incorporate some form of machine learning capabilities, empowering the application itself and making it smarter. In this series, you'll learn how the ML.NET framework has been designed to democratise the art of machine learning, converting it into a technology available to all developers around the globe. You'll also see practical examples of how you can implement a solution in the ML.NET framework, using a real-world scenario and 2 different approaches: low code and code-heavy. What is the session about? This session is an introduction to building a text classification model with Model Builder in ML.NET, able to classify if a news is fake or not. Who is it aimed at? This session is for students, early career and professionals who are interested in setting themselves up to build smart apps using ML.NET Why should you attend? If you think of yourself as a developer or an aspiring software engineer, you might see machine learning as a separate art, practiced by an elite of data scientists and statisticians, and you might be uncertain about how it fits into application development. Attend this session if you wish to find an answer to your doubts. Speaker bio's Carlotta Castelluccio, Cloud Advocate Microsoft Carlotta Castelluccio is a Cloud Advocate at Microsoft, focused on Data Analytics and Data Science. As a member of the Developer Relationships Academic team, she works on skilling and engaging educational communities to create and grow with Azure Cloud, by contributing to technical learning content and supporting students and educators in their learning journey with Microsoft technologies. Before joining the Cloud Advocacy team, she worked as an Azure and AI (ARTIFICIAL INTELLIGENCE) consultant in Microsoft Industry Solutions team. Connect with Carlotta https://www.linkedin.com/in/carlotta-castelluccio/ https://twitter.com/carlottacaste Liam Hampton, Regional Cloud Advocate, Microsoft Liam is a Regional Cloud Advocate at Microsoft. He is an IoT hobbyist, a podcast co-host and a Software Engineer with multiple Professional Cloud Certifications. He is passionate about cloud computing, clean code and creating simple and concise content for others. When he is not writing code or presenting, you'll either find him searching for the next best eatery in London, studying different cultures or at the airport jetting of to explore the next city on his TODO list. Connect with Liam Twitter: https://twitter.com/liamchampton Linkedin: https://www.linkedin.com/in/liam-conroy-hampton/

6:00 odp. - 7:00 odp. (UTC)

This event is a part of "Getting Practical with ML.NET" series Series Description In the near future, every application on every platform will incorporate some form of machine learning capabilities, empowering the application itself and making it smarter. In this series, you'll learn how the ML.NET framework has been designed to democratise the art of machine learning, converting it into a technology available to all developers around the globe. You'll also see practical examples of how you can implement a solution in the ML.NET framework, using a real-world scenario and 2 different approaches: low code and code-heavy. What is the session about? The session is aimed at showing you how to deploy and consume a text classification ML model in a web application. Who is it aimed at? This session is for students, early career and professionals who are interested in setting themselves up to build smart apps using ML.NET Why should you attend? If you think of yourself as a developer or an aspiring software engineer, you might see machine learning as a separate art, practiced by an elite of data scientists and statisticians, and you might be uncertain about how it fits into application development. Attend this session if you wish to find an answer to your doubts. Speaker bio's Carlotta Castelluccio, Cloud Advocate Microsoft Carlotta Castelluccio is a Cloud Advocate at Microsoft, focused on Data Analytics and Data Science. As a member of the Developer Relationships Academic team, she works on skilling and engaging educational communities to create and grow with Azure Cloud, by contributing to technical learning content and supporting students and educators in their learning journey with Microsoft technologies. Before joining the Cloud Advocacy team, she worked as an Azure and AI (ARTIFICIAL INTELLIGENCE) consultant in Microsoft Industry Solutions team. Connect with Carlotta https://www.linkedin.com/in/carlotta-castelluccio/ https://twitter.com/carlottacaste Liam Hampton, Regional Cloud Advocate, Microsoft Liam is a Regional Cloud Advocate at Microsoft. He is an IoT hobbyist, a podcast co-host and a Software Engineer with multiple Professional Cloud Certifications. He is passionate about cloud computing, clean code and creating simple and concise content for others. When he is not writing code or presenting, you'll either find him searching for the next best eatery in London, studying different cultures or at the airport jetting of to explore the next city on his TODO list. Connect with Liam Twitter: https://twitter.com/liamchampton Linkedin: https://www.linkedin.com/in/liam-conroy-hampton/