It’s no exaggeration to say that Machine Learning (ML) and Deep Learning (DL) are quickly changing the way we live. Things we are accustomed to today are things we could only dream of 10 years ago. As ML is becoming more and more mainstream, you may be asking yourself how do I get started?

Historically, many of the tools and libraries used to train a model have been found in the Python and R communities (e.g. Scikit Learn, PyTorch, TensorFlow), but what if you’re a .NET Developer? Allow me the pleasure to introduce ML.NET!

ML.NET is an open-source, cross-platform machine learning library, specifically built to enable .NET developers to train their own custom machine learning models in C# or F#.
In this workshop we’ll cut through all the foreign jargon around machine learning and give you some hands-on experience training custom models in C# using interactive exercises.

What you’ll learn:
- Understand the concepts around Machine Learning and Deep Learning
- Learn how to train a custom machine learning model using ML.NET in C# and AutoML
- Learn how to use transfer learning to train deep neural networks for computer vision
- Understand when and how we can leverage Jupyter Notebooks with ML.NET
- Explore ways we can deploy our custom machine learning model to production
- Explore how to set up a real-time data pipeline in Azure for real-time inference

What you’ll need to bring
- A laptop
- A free Azure subscription
- An installation of the .NET Core SDK
- An installation of Visual Studio Code