San Francisco, California
London, United Kingdom
Machine learning is the art of writing program that become better at performing tasks using data. In this hands-on workshop you will learn how to use the power of F# by building simple but effective machine learning predictive models and solving real-world problems. In the process, you will learn fundamental concepts and methods of machine learning that are broadly applicable by software engineers, and gain a solid foundation to start writing clean and effective F# code.
Instructors: Tomas Petricek, Mathias Brandewinder
- No prior F# experience needed.
- No prior machine learning experience needed.
- Previous programming experience required.
- Experience with .NET and C# is desirable.
Laptop with F# installed (see fsharp.org for installation instructions)
What you will learn
- Gain comfort with F# syntax, tools and concepts,
- Understanding what Machine Learning is and what it means to "do machine learning",
- Using F# collections, tuples and pattern matching to manipulate data efficiently,
- Using the F# scripting environment to explore and code interactively,
- Using Type Providers to simplify data access,
- Using cross validation and grid search to tune a Machine Learning model,
- Learn the nuts and bolts of a couple of different models covering different domains
- Coffee will be available throughout the day
- Pastries will be served in the morning
- A light lunch will be provided