Name: PyData Edinburgh: From Software Engineering to Machine Learning
Start: 2018-04-05T18:15:00+01:00
End: 2018-04-05T21:00:00+01:00
Location: The Data Lab

And we're really back this time! After snow cancelled play the last time, we're hopeful that we're back on track for our next PyData Edinburgh meetup.

We'll have our regular update on the PyData community, lightning talks and we're delighted to say we have two main speakers — Ewan Nicolson, who should have been with us last time, Principal Data Scientist at Skyscanner here in Edinburgh and Andy McMahon, Head of Data Science & Machine Learning at Streamba in Glasgow.

TALK DETAILS
=============

Great Techniques I’m Stealing from Software Engineers
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Presenter: Ewan Nicolson

Ewan has been working professionally with numbers and computers for the past 12 years. During the past 5 years at Skyscanner he’s seen the data team grow from 2 analysts based in Edinburgh, to a global team of 25+ data scientists making global impact.

Description:

Data science is a young field, and we can learn lots from people who have gone before us. My colleagues in software development have taught me lots: agile methods, testing, continuous deployment, and so on. I’m going to talk about how we can apply these to data science to make our field more mature.

Machine Learning in Production with Python-Based Microservices
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Presenter: Andy McMahon

Andy is Head of Data Science & Machine Learning at Streamba, a start-up in Glasgow which develops cutting edge software solutions for the energy industry. His work in the VOR team spans the spectrum of predictive, prescriptive and descriptive analytics with a particular focus on production ready machine learning solutions. He's a keen Pythonista and does almost all of his development in Python. Recently he has been exploring Scala and Java for developing machine learning system.

Description:

Among the many challenges I've faced at Streamba is how do you take your shiny new ML model and actually put it into production? In this talk I'll discuss some of the different ways you can do this, with a focus on the cloud-based microservice architecture. I'll then (time permitting) show a running example of this with a very simple ML microservice running in the cloud. Hopefully you'll come away with a better idea of how to take your Python scripts and ML code and convert them into a running service that brings value to customers and internal stakeholders.

LIGHTNING TALKS
==================
Have you a project you want to highlight? A new library you want to show? Lightning talks have been really popular at other PyData meetups, so let's get the ideas flowing in Edinburgh!

Just sign up on the evening: anything goes (within reason!) and no more than 5 minutes long — we'll be bringing the alarm clock!

LOGISTICS
===========
We're back the The Data Lab this month — please note all attendees MUST sign up to the Meetup to be admitted.

Doors open at 1815 with refreshments, talks kick off with an update on news relating to the PyData community at 1845 and we'll end the evening with pizza and more refreshments, wrapping up by 2100.

SPONSORS & REFRESHMENTS
=============================
As always, thanks to our sponsors — Cathcart Associates (https://www.cathcartassociates.com) for providing us with drinks & pizzas again, and The Data Lab for providing the venue.

We are looking to find other sponsors to help support us running these meet ups — if you are interested, or think your company could be, please speak to one of the organisers on the night, or get in touch through Meetup.

CODE OF CONDUCT
====================
The PyData Code of Conduct governs this meetup. ( http://pydata.org/code-of-conduct.html ) To discuss any issues or concerns relating to the code of conduct or the behavior of anyone at a PyData meetup, please contact NumFOCUS Executive Director Leah Silen (+1 512-222-5449; leah@numfocus.org) or the group organizer.

Matthew Higgs

Martina Pugliese

Sam Rhynas

Nick Radcliffe

Thomas Kober

PyData Edinburgh

Technology

Predictive Analytics

Artificial Intelligence

Data Management

Python

Statistical Computing

Big Data

High Scalability Computing

Machine Learning

Data Analytics

Data Visualization

Data Mining

Data Science

Open Source Python

Data Science using Python

PyData Edinburgh: From Software Engineering to Machine Learning

The Data Lab

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PyData Edinburgh: From Software Engineering to Machine Learning

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