Data Lab seeking analysts, developers, engineers, and scientists for inaugural event
Data analysts, developers, engineers and scientists from the public sector, academia, and industry are invited to submit proposals to present at DataTech19, the newest platform at the annual Data Fest, run by The Data Lab.
The one-day data science conference is aimed at a technical audience, and will provide Scotland’s data community with a forum to share emerging research, share technical expertise, and engage in networking. DataTech will include presentations, lightning talks and posters from successful submissions, alongside talks from keynote speakers.
Dr Caterina Constantinescu, of The Data Lab is Chair of DataTech’s organising committee and explained: “DataTech has been established due to feedback at previous editions of DataFest expressing a demand for deeper technical content. It will complement the other events of Data Fest that have been so successful to date. DataTech caters to the increasing technical appetite of Scotland’s active, dynamic data ecosystem.
“We’re looking for submissions covering a range of topics, from scaling algorithms, software and hardware to cope with large amounts of data, machine learning techniques, to deep learning and reproducible and collaborative data science, as well as many more.
“In addition, we also encourage submissions with the potential to bridge multiple topics of wide interest. We’re excited about the prospect of creating an insightful and engaging day for attendees, and urge data specialists to get in touch and tell us about their work – we want to hear from you.”
The first confirmed keynote speaker for DataTech19 is Jared Lander, Chief Data Scientist of Lander Analytics, a data science consultancy based in New York City, and Adjunct Professor of Statistics at Columbia University. Jared also organises the New York Open Statistical Programming Meetup and the New York R Conference. The applications of his work on data management, multilevel models, machine learning, generalized linear models and statistical computing have ranged from music and fund raising, to finance and humanitarian relief efforts.
He is also the author of R for Everyone: Advanced Analytics and Graphics and is creating a course with DataCamp on Lasso and Elastic-Net Regularized Generalized Linear Models via R package `glmnet`. Recently, he has spoken on topics such as parallel computing in R, deep learning, machine learning in R and time series in R at Strata in New York and London and ODSC London this year.
Visit here for information on how to submit a proposal.
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