From joe.jasinski at gmail.com Mon Apr 10 23:03:07 2017 From: joe.jasinski at gmail.com (Joe Jasinski) Date: Mon, 10 Apr 2017 22:03:07 -0500 Subject: [ChiPy-announce] PyLadies visit ChiPy: April 2017 Meeting Message-ID: 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 or via our Meetup 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 -------------- next part -------------- An HTML attachment was scrubbed... URL: