C#/ML.NET Machine Learning MasterClass

In this 2-day training you will learn how to build machine learning applications in C# with Microsoft’s new ML.NET library. You will learn how to prepare a data set, load and process it, and design and train a machine learning model to generate useful predictions from the data. The course will provide a solid foundation of machine learning (regression, classification and clustering) and also cover advanced applications like using deep convolutional neural networks to detect objects in images. You will learn how to build advanced AI applications with only a few lines of C# code. We will cover many use cases like trend prediction, anomaly detection,text analysis, computer vision, and many others. During the course Mark Farragher will share many tips and tricks on how you can start introducing AI and data science functionality to your business today. Technology Platform This course uses NET Core version 3.0 and Microsoft Visual Studio Code. Both Windows 10, OS/X, and Ubuntu L... Read more

In this 2-day training you will learn how to build machine learning applications in C# with Microsoft’s new ML.NET library. You will learn how to prepare a data set, load and process it, and design and train a machine learning model to generate useful predictions from the data. The course will provide a solid foundation of machine learning (regression, classification and clustering) and also cover advanced applications like using deep convolutional neural networks to detect objects in images. You will learn how to build advanced AI applications with only a few lines of C# code. We will cover many use cases like trend prediction, anomaly detection,text analysis, computer vision, and many others. During the course Mark Farragher will share many tips and tricks on how you can start introducing AI and data science functionality to your business today. Technology Platform This course uses NET Core version 3.0 and Microsoft Visual Studio Code. Both Windows 10, OS/X, and Ubuntu Linux are supported. The source code of all demos will be made available to participants.