Understanding cancer behaviour with F#
Please log in to watch this conference skillscast.
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#.
YOU MAY ALSO LIKE:
- Keynote: The Bottom of the Iceberg: Enabling Data Science Research with F# (SkillsCast recorded in April 2019)
- Real World Kotlin Development Workshop (in London on 22nd - 23rd October 2019)
- Leonardo De Marchi's Deep Learning Fundamentals (in London on 22nd - 23rd October 2019)
- Clojure eXchange 2019 (in London on 2nd - 3rd December 2019)
- Scala eXchange London 2019 (in London on 12th - 13th December 2019)
- Countdown to Big Data LDN (in London on 17th October 2019)
- Reinforcement Learning Journal Club (in London on 17th October 2019)
- Keynote: (Programming Languages) in Agda = Programming (Languages in Agda) (SkillsCast recorded in October 2019)
- Keynote: Haskell is a Great Host (SkillsCast recorded in October 2019)
Thanks to our sponsors
Understanding cancer behaviour with F#
Evelina Gabasova
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.