[ChiPy-announce] PyLadies visit ChiPy: April 2017 Meeting

[Joe Jasinski]

All,

This month, PyLadies and ChiPy will join together in a combined meeting
that's sure to be exciting!  We have a great speaker lineup and, as always,
lots of enthusiasm for Python. Join us for Python, food, and fellowship.
And don't forget to stop by the welcome table to say hello and meet some
friendly faces!

Hope to see you there!



*When:*Thursday April 13th
6:00pm:  Doors open; food arrives
6:30pm:  Welcome table - meet new people
7:00pm:  Talks Start promptly at 7


*How:*You can rsvp at chipy.org <http://www.chipy.org/> or via our Meetup
<https://www.meetup.com/_ChiPy_/events/238363273/> group.

*Where:*
Deloitte
111 S Wacker
15th floor Divisible Training Room
Chicago, IL 60606


*What:*

   - *Introduction to Project Magellan *
   By: Ancy Phillip
   Experience Level: Intermediate
   Day by day, the world is becoming more data driven, making data science
   extremely popular. Data Wrangling , Data Analysis form the two important
   stages in any Data Science problem and Entity Matching(EM) is extremely
   critical in the latter phase. EM has been a long-standing challenge in data
   management. Most current EM works focus only on developing matching
   algorithms. A solution to this, Magellan, is a new kind of EM systems, open
   sourced on top of the PyData eco-system. Magellan is novel in four
   important aspects. (1) It provides how-to guides that tell users what to do
   in each EM scenario, step by step. (2) It provides tools to help users do
   these steps; the tools seek to cover the entire EM pipeline, not just
   match- ing and blocking as current EM systems do. (3) Tools are built on
   top of the data analysis and Big Data stacks in Python, allowing Magellan
   to borrow a rich set of capabil- ities in data cleaning, IE, visualization,
   learning, etc. (4) Magellan provides a powerful scripting environment to
   fa- cilitate interactive experimentation and quick “patching” of the
   system. Magellan is used at Walmart Labs, Johnson Controls, Marshfield
   Clinic and as a teaching tool in UWM classes.
   - *How a Study Group Can Help a ML Beginner Learn Deep Learning*
   By: Apurva Naik
   Experience Level: Novice
   Deep learning has never been accessible to people with limited ML
   experience. All over the internet, beginners only come across
   discouragement, exclusion and elitism when they express an interest in
   doing deep learning. A recently released MOOC, fast.ai is specifically
   designed for those with some coding experience. The MOOC's creators use a
   hands-on approach of teaching that focuses on coding first and
   understanding later. I will talk about the balancing act between work,
   family and passion projects, how my study buddies help me stay on track,
   and what we're doing to help others learn.
   - *Trolling databases with Python! *
   By: Loren Velasquez
   Experience Level: Novice
   You are the data troll who allows what data can be pushed up. All data
   requests are in your hands but first you need to become an official data
   troll by getting your information in the data troll table (you need to be
   legit in the database or else it didn't happen). This is a super simple
   example of how Python can be friends with database, today we’ll look at
   Postgres!
   - *TDD with PyTest*
   By: Sand Ip
   Experience Level: Novice
   PyTest helps Python developers with test-driven development, continuous
   integration, and quality engineering. In this talk we’ll cover setup, data
   fixtures, case types, and results interpretation by walking through a
   PyTest demo.
   - *Grok the GIL: Write Fast And Thread-Safe Python*
   By: A. Jesse Jiryu Davis
   Experience Level: Intermediate
   This is a sneak preview of a talk accepted to PyCon 2017, this June in
   Portland. A. Jesse Jiryu Davis is a prominent open source developer who has
   spoken at the last three PyCons, so this talk promises to be thorough,
   technical, and fun. He describes the talk thus: "I wrote Python for years
   while holding mistaken notions about the Global Interpreter Lock, and I've
   met others in the same boat. The GIL's effect is simply this: only one
   thread can execute Python code at a time, while N other threads sleep or
   await network I/O. Let's read CPython interpreter source and try some
   examples to grok the GIL, and learn to write fast and thread-safe Python."
   Jesse is a Staff Engineer at MongoDB in New York City specializing in C,
   Python, and async. Lead developer of the MongoDB C Driver libraries libbson
   and libmongoc. Author of Motor, an async MongoDB driver for Tornado and
   asyncio. Contributor to Python, PyMongo, MongoDB, Tornado, and asyncio.
   Co-author with Guido van Rossum of "A Web Crawler With asyncio Coroutines",
   a chapter in the "500 Lines or Less" book in the Architecture of Open
   Source Applications series.
   - *Python Software Foundation Update + how you can be involved! *
   By: Lorena Mesa
   Experience Level: Novice
   What's happening at the Python Software Foundation? Look no further
   Python Software Foundation Director Lorena Mesa will run through an update!
   Information about elections, a new PyCon organizers manual, the PSF Code of
   Conduct Committee will be briefly covered.



Thank you always to all our sponsors, including our Diamond sponsor: Metis.
Also thank you to our Platinum sponsors: Braintree, Imaginary
Landscape, Signature
Consultants, and Telnyx.

Please be aware of our code of conduct http://www.chipy.org/pages/conduct/



-- 
Joe J. Jasinski
www.joejasinski.com
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