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by Marek Kubica
With industry adoption rising, startups picking it, new books being written and released, the underdog of statically typed functional programming languages, OCaml, is rapidly changing for the better. 2015 might be the year for you to pick it up. We will mention some of the reasons, OCaml might be just what you have been missing out on. As the ecosystem has grown organically, there is a lot of things building on top of each other that might be confusing to a newcomer and there is not yet a “standard way of doing things”. We will describe how to start an OCaml project: what tools are available, how to structure code, what libraries are available, editor integration, community support (IRC and mailing lists), documentation, continuous integration. We will also take a look at what's still lacking.
Data science is emerging as a hot topic across many areas both in industry and academia. In my research, I’m using machine learning methods to build mathematical models for cancer cell behaviours. But using today’s data science tools is hard – we waste a lot of time figuring out what format different CSV files use or what is the structure of JSON or XML files. Often, we need to switch between Python, Matlab, R and other tools to call functions that are missing elsewhere. And why are many programming languages used in data science missing tools standard in modern software engineering?
In this talk I’ll look at data science tools in F# and how they simplify the life of a modern scientist, who heavily relies on data analytics. F# provides a unique way of integrating external data sources and tools into a single environment. This means that you can seamlessly access not only data, but also R statistical and visualization packages, all from a single environment. Compile-time static checking and rich interactive tooling gives you many of the standard tools known from software engineering, while keeping the explorative nature of simple, scripting languages.
Using examples from my own research in bioinformatics, I’ll show how to use F# for data analysis using various type providers and other tools available in F#.
Making great games is all about fast iteration. Giving the designers and content creators the ability to quickly test an idea and then grow that idea organically is critical to finding the fun. That means that we as developers need to make tools that make their workflows as painless and transparent as possible.
Over the last year, we have been using F# in our game and this talk is a short reflection on how that has turned out.
We'll talk about: the language, the ecosystem, the tooling and the community with live examples from the game and the tool chain
26th–27th February 2015