Halifax Data Science Meetup

November 27, 2018 - November 27, 2018 (6:00 pm - 9:00 pm)


Come talk data science with us on Tuesday November 27th! We'll meet up at 6:00 pm, and kick off talks at around 6:30 pm.

Refreshments kindly sponsored by Affinio — check out https://www.affinio.com/careers/ to learn more about their current job postings!

*****
Space is limited so be sure to RSVP. Also please cancel your RSVP in case you find you are not coming, regardless how close to the meetup date you find out!
*****

Talks:

1. Dr. Danny Silver is the Director of the Acadia Institute for Data Analytics. He is also a professor in and the former Director of the Jodrey School of Computer Science at Acadia University. His areas of research and application are machine learning, data mining, and data analytics and is well published with recent best paper awards at the FLAIRS-2016 and CASCON-2017 conferences. His talk will review the basic concepts of Transfer Learning, Consolidation and Lifelong Machine Learning. He will show how deep learning has proven the value of developing internal representations and rich feature sets from unsupervised learning as well as supervised multiple task learning (MTL). He will review context-sensitive MTL and show how it can be used to develop deep Lifelong Machine Learning systems that can learn diverse families of functions and train architectures with multiple input/output modalities. Finally, he will discuss how Lifelong Machine Learning is providing insights into how to develop common knowledge representation for Learning to Reason.

2. Daniel Arantes is a freelancer with more than 15 years of experience, and more than 5 years experience working in R. Has worked with Atlantic Lotto Corporation on a project involving basket analysis of over 30M transactions (over 120M rows). His talk will focus on R's data.table, detailing a tool that receives much less attention than it deserves. For R users it is a solid tool that is available for over 10 years and has zero dependencies of external packages and delivers by far the best performance. For Python users it is a new tool for data manipulation. Coming into Python backed by H2o.ai and is being implemented based on the same principles and design as implemented for R.

See you there!


Go back