This document summarizes the inaugural talk for the Data Science Milan meetup group. It provides background on the speaker, Gianmario Spacagna, including his work experience and interests in machine learning systems, Scala, and the Professional Data Science Manifesto. It also gives an overview of the Data Science Milan meetup group, including its goals of promoting data-driven innovation and knowledge sharing among its members. Additionally, it outlines partnerships with Big Data consultancy startups and other meetup groups. Finally, it summarizes the results of an initial interests survey of group members.

1. Data Science Milan
Inaugural Talk
Gianmario Spacagna
19/05/2016

2. About me @gm_spacagna
• Background in Telecommunications and Distributed Systems
• (University of Cassino, Polytechnic of Turin, KTH of Stockholm)
• Experience in a few industries:
• Predictive Marketing (AgilOne, StreamSend)
• Social/Travel (Random Break)
• Cyber Security (Cisco)
• Financial Services (Barclays)
• Automotive (Pirelli)
• Areas of interest
• Building production-ready and scalable machine learning systems
• Functional Programming, Scala and Apache Spark
(check out sparkz on github)
• Contributor of the Professional Data Science Manifesto
(www.datasciencemanifesto.org)
• Organizing events and meet-ups 

3. About us
• 159 members on meetup
• 79 on LinkedIn
• Community of Data
Scientists, practitioners
and enthusiasts based in
the Milan area
• No profit, open group
• Goal:
• Discuss and promote data-
driven innovation
• Collaboration and sharing
of knowledge

4. Partnerships
• Diego Liberati, host
• , Big Data consultancy start-up
• Milan High Tech Meetup group
(www.meetup.com/Milan-High-Tech-Meetup)

5. Background and Interests Survey
• 80 responses so far, pretty good!
• http://goo.gl/forms/3xvJMX4KvO
• Most popular:
• Role: Data Scientist, Developer, Student/PhD, Data
Engineer
• Experience: mid-senior, junior, student/intern
• Languages: Python, R, Java, C, Matlab, Scala
• Technologies SQL/RDBMS, Notebooks, viz libs, Spark,
Hadoop
• More predictive analytics than descriptive
• Topics: Machine Learning & Deep Learning, Production
use-cases, Functional Programming, Streaming, NLP
• Summary will be available soon…

6. #datasciencemilan
• If you haven’t done yet, remember to join us on
http://www.meetup.com/Data-Science-Milan/
And our LinkedIn group:
https://www.linkedin.com/groups/8497363