Saturday 24th October, 2015
12:00pm to 1:00pm
MongoDB is a flexible, scalable, and ease to use way of storing your large data set. Python provides many useful data science tools (e.g. NumPy, SciPy, Scikit-learn, etc.). Unfortunately, they don't work well together, one of the bottlenecks is the inefficiency of loading MongoDB data into NumPy array.
This talk will discuss the concerns for creating operational data analytic pipelines, introduce Monary as alternative for loading data into NumPy, and give examples of accessing data with Monary, as well as how to build scalable data analysis pipelines using these open source tools.
"Eoin works at MongoDB working with clients using MongoDB helping to guide and troubleshoot problems as well as providing architectural recommendations. He previously worked in research commercialisation and led teams in TSSG (mobile services) and ICHEC (HPC/parallel programming) focused on commercial consultancy projects. He spent almost a decade as a researcher in interaction design. He has given talks on topics from machine learning to behaviour design to mobile services and HPC.
Eoin holds a BSc in Computer Systems from UL, a PGDip in Technology Commercialisation from NUIG as well as a MSc and a PhD in Computer Science from UL."
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