.NET Rocks!

R for the .NET Developer with Jamie Dixon and Evelina Gabasova

Episode #1327 Wednesday, July 27, 2016

Ready to learn R? While at NDC Oslo, Carl and Richard sat down with Jamie Dixon and Evelina Gabasova to talk about what .NET developers need to know to get conversant in R. Data science represents a huge opportunity for developers these days, helping businesses actually take advantage of the data the company has. Jamie comes at R from a traditional .NET developer perspective, talking about how there are some skills (like source control and testing) that developers have more experience with than most data science folks. Evelina talks about the academic side of using R, learning statistical modeling and how to talk to data science experts when you're a developer. There's a great community out there to help you learn more and focus on the right things - join in!


Jamie Dixon

Jamie Dixon has been writing code for as long as he can remember and has been getting paid to do it since 1995. He was using C# and javascript almost exclusively until discovering F#.About three yers ago, he started working with R and and now combines all four languages for the problem at hand. He has a passion for discovering overlooked gems in data sets and merging software engineering techniques to scientific computing. Jamie has a BSCS in Computer Science and a Masters in Public Health. He is the former Chair of his town's Information Services Advisory Board and is an outspoken advocate for Open Data.

Evelina Gabasova

Evelina Gabasova is a machine learning researcher working in bioinformatics and statistical genomics. She is developing mathematical models which integrate different types of genomic data to distinguish cancer subtypes. She studied computational statistics and machine learning at University College London and currently she is finishing her PhD at Cambridge University in the MRC Biostatistics Unit. Evelina has used many different languages to implement machine learning algorithms, such as Matlab, R or Python. In the end, F# is her favourite and she uses it frequently for data manipulation and exploratory analysis. She writes a blog on F# in data science at evelinag.com. You can also find her on Twitter as @evelgab.


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