Data science with F#: Social network analysis - Evelina Gabasova

Online social media connect us all. How can we use the information that is hidden in our social networks? For example, do you know who is your most influential follower on Twitter? 
We will work through the whole process of social network analysis: from downloading connections using Twitter REST-based API, to implementing our own PageRank algorithm which finds the most central Twitter accounts. In the process you’ll see how we can use F# type providers to access data and harness the power of the statistical language R to run some machine learning algorithms. 
At the end, you’ll know how to run your own analysis on data from Twitter and how to use data science tools to gain insights from social networks. 

Evelina is a PhD student in bioinformatics at University of Cambridge. She is interested in data science and all things machine learning.

Please register with Skills Matter too:

P.S. There's a special offer of 20% off this year's Progressive F# Tutorials for F#unctional Londoners members before Evelina's talk. Use Promo Code F#UNCTIONAL-20 when registering:

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  • Evelina G.

    Slides and code from my talk are now on GitHub­

    2 · September 26

  • Erik C.

    Had a last minute call-out, so couldn't attend. Would however love to see the slides if available. [masked]

    September 25

  • Adam M.

    Great presentation! Thanks Evelina

    September 25

  • Dr Nigel G.

    Excellent example of using F# to approach simple GRAPH applications

    1 · September 25

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