A SkillsCast for this session is not available.
Machine learning and functional programming are two exciting programming trends of the recent years. To a newcomer, both of these may sound very complicated. If you attend this workshop, you'll see that this could not be further from the truth. We will look at solving real-world machine learning problems with the functional-first programming language F# and you'll see that this is a perfect match - functional programming makes it easy to express machine learning algorithms in a clear and easy to understand way.
In this workshop, we'll implement a machine learning algorithm for automatically detecting the language of text, using pages downloaded from Wikipedia (using an F# web crawler) as a training data set. Along the way you'll learn about machine learning concepts, the F# language and the functional approach to data processing.
What you can expect to learn:
- How to use F# to implement machine learning algorithms
- Writing simple code using functional style
- The core ideas behind artificial neural networks
No prior machine learning or F# knowledge is needed.
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Evelina is a Senior Research Data Scientist at The Alan Turing Institute, the UK's national centre for data science and artificial intelligence. She is passionate about making data science understandable and accessible to everyone. She originally started as a programmer but got interested in machine learning early on and did a mathematics PhD at the University of Cambridge. During her PhD, she worked on Bayesian models for unsupervised learning that integrate heterogeneous biomedical datasets. After that, she worked in cancer research at the MRC Cancer unit in Cambridge, where she focused on helping biologists analyse genomic data.