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.
Matthew Moloney discusses using F# and .NET inside Excel, demonstrating doing big data, cloud computing, using GPGPU and compiling F# Excel UDFs.
Mike Falanga shows several C# and F# solutions to common programming problems, comparing how well each language enhances the ability to draw accurate conclusions about the code.
Phil Trelford describes and demonstrates areas where F# excels, such as domain modeling, computation and concurrency.
Colin Gravill talks about how using F# to construct a shared analysis engine and the languages used to make the individual tools.