Andrea Magnorsky discusses active patterns, computation expressions, parsers, using type providers and more. These language features help make code simpler and easier to maintain.
Felienne Hermans explains how she used F# to determine if the game Quarto can end up in a tie or if there is always a winner. The technique used can be applied to scheduling and register allocation.
Phillip Trelford shows through live demos data structures that are orders of magnitude more performant than lists.
Alena Hall presents various machine learning algorithms available in Accord.NET - a framework for machine learning and scientific computing in .NET.
Daniel Egloff overviews Alea, an F# alternatives to CUDA C/C++ and OpenCL C++, showing how to write GPU scripts and perform dynamic compilation in F#.
Evelina Gabasova explains how to run a social network analysis on Twitter and how to use data science tools to find out more about followers.
Phillip Trelford explains how compilers work with live code samples, primarily in F# and C#, covering language design and parsing, all-the-way through to emitting code.
Mark Seemann uses F# to demonstrate how to use functional design with TDD to remove the need for Mock objects.
Don Syme makes a journey through the modern programming landscape and the F# approach to research, language design, interoperability, tooling and community.
Tomas Petricek introduces F#’s capabilities in dealing with scientific data: type providers -CSV, XML, JSON, REST-, interactive development, data visualization libraries, integration with R or MathLab
Phil Trelford demoes accessing a variety of data sources via F# Type Providers.
Felienne Hermans introduces BumbleBee, a refactoring and metaprogramming spreadsheets tool based on a DSL that can perform transformations against spreadsheet formulas.