See Also:
Upcoming Meetings
All Recent Topics
Thu, Apr 13 2017 at 06:00 PM at Deloitte
Introduction to Project Magellan
(25 Minutes)
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.
(25 Minutes)
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.
Grok the GIL: Write Fast And Thread-Safe Python
(30 Minutes)
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.
(30 Minutes)
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.
How a Study Group Can Help a ML Beginner Learn Deep Learning
(5 Minutes)
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.
(5 Minutes)
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.
Python Software Foundation Update + how you can be involved!
(10 Minutes)
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.
(10 Minutes)
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.
TDD with PyTest
(10 Minutes)
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.
(10 Minutes)
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.
Trolling databases with Python!
(7 Minutes)
By: Loren Velasquez
Experience Level: Novice
Slides Link
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!
(7 Minutes)
By: Loren Velasquez
Experience Level: Novice
Slides Link
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!
223 Python enthusiasts attended this meeting.
Thu, Mar 09 2017 at 06:00 PM at Braintree
How To Develop and Deploy Faster using Python APIs
(20 Minutes)
By: Paul
Experience Level: Intermediate
Building and deploying applications has never been easier, especially with the proliferation of APIs. In this talk, I will share the 4 concepts that will allow Python developers to quickly learn and use any Python-based API. The target audience for this talk are intermediate newbies who have a couple of projects under their belt.
(20 Minutes)
By: Paul
Experience Level: Intermediate
Building and deploying applications has never been easier, especially with the proliferation of APIs. In this talk, I will share the 4 concepts that will allow Python developers to quickly learn and use any Python-based API. The target audience for this talk are intermediate newbies who have a couple of projects under their belt.
Quick prototyping with redis-helper
(30 Minutes)
By: Kenneth Wade
Experience Level: Novice
In this talk, I will demonstrate some uses of https://pypi.python.org/pypi/redis-helper and how you can easily store, index, and modify Python dicts in Redis. Some asciinema demos are available at https://asciinema.org/~kenjyco
(30 Minutes)
By: Kenneth Wade
Experience Level: Novice
In this talk, I will demonstrate some uses of https://pypi.python.org/pypi/redis-helper and how you can easily store, index, and modify Python dicts in Redis. Some asciinema demos are available at https://asciinema.org/~kenjyco
How I Taught My Dog To Text Selfies
(30 Minutes)
By: Greg Baugues
Experience Level: Novice
This talk is is for Python developers who would like to get started with hardware hacking but have been too intimidated in the past to do so. Also, it's for people who like dogs and/or selfies. Using a Raspberry Pi, Python, Twilio, and a big red button, I taught my dog to text selfies. In this talk, which features 25 minutes of live coding, we'll build the hardware hack from scratch. Developers will walk away knowing how to use Python to interact with Twilio and the Raspberry Pi's GPIO pins. A video of this hack was featured on Mashable and was watched over 2.5M times.
(30 Minutes)
By: Greg Baugues
Experience Level: Novice
This talk is is for Python developers who would like to get started with hardware hacking but have been too intimidated in the past to do so. Also, it's for people who like dogs and/or selfies. Using a Raspberry Pi, Python, Twilio, and a big red button, I taught my dog to text selfies. In this talk, which features 25 minutes of live coding, we'll build the hardware hack from scratch. Developers will walk away knowing how to use Python to interact with Twilio and the Raspberry Pi's GPIO pins. A video of this hack was featured on Mashable and was watched over 2.5M times.
45 Python enthusiasts attended this meeting.
Thu, Feb 09 2017 at 06:00 PM at Loyola University (Schreiber Center)
Unsupervised machine learning in engineering and neuroscience: applications of ICA
(90 Minutes)
By: Mark V. Albert, Pavan Ramkumar, Anne Zhao, Jorge Yanar
Experience Level: Intermediate
This talk with be a set of four short presentations guiding everyone through three applications of unsupervised machine learning. We begin with the classic cocktail party problem - how to automatically separate mixed voices recorded by microphones - presented by Jorge Yanar. This will be followed by a brief, intuitive explanation of the algorithm used to perform the task - Independent Components Analysis (ICA) described by Professor Mark Albert. Dr. Pavan Ramkumar will demonstrate how the same technique is applied to filter unwanted noise during neural recordings using EEG, and Anne Zhao will end with a demonstration of how the same coding strategy has led to insights in how the brain encodes sensory information in the early auditory and visual systems. Her demo will allow participants to develop their own simulated neural codes for processing visual images. The brief talks will consist of a Jupyter notebook for running code and displaying results. For those who wish to run the examples during the talk, it will be necessary to install Jupyter running Python version 3 (the Anaconda Python distribution is recommended to set this up). Links and setup instructions will be given prior to the talks for people to follow along on their laptops and try the examples on their own if desired.
(90 Minutes)
By: Mark V. Albert, Pavan Ramkumar, Anne Zhao, Jorge Yanar
Experience Level: Intermediate
This talk with be a set of four short presentations guiding everyone through three applications of unsupervised machine learning. We begin with the classic cocktail party problem - how to automatically separate mixed voices recorded by microphones - presented by Jorge Yanar. This will be followed by a brief, intuitive explanation of the algorithm used to perform the task - Independent Components Analysis (ICA) described by Professor Mark Albert. Dr. Pavan Ramkumar will demonstrate how the same technique is applied to filter unwanted noise during neural recordings using EEG, and Anne Zhao will end with a demonstration of how the same coding strategy has led to insights in how the brain encodes sensory information in the early auditory and visual systems. Her demo will allow participants to develop their own simulated neural codes for processing visual images. The brief talks will consist of a Jupyter notebook for running code and displaying results. For those who wish to run the examples during the talk, it will be necessary to install Jupyter running Python version 3 (the Anaconda Python distribution is recommended to set this up). Links and setup instructions will be given prior to the talks for people to follow along on their laptops and try the examples on their own if desired.
187 Python enthusiasts attended this meeting.
Thu, Jan 12 2017 at 06:00 PM at DeskLabs
Mentorship Program Finals
By:
The largest ever cadre of ChiPy Mentorship participants meet to present their findings after 13 weeks of study with their mentors. You'll see demos and discussion for entry level projects, web development projects and data science experiments gone mad with the power of Python. Each presenter gets five minutes to tell the story of their journey and what they produced. Plus amazing prizes and announcements on how to apply for the spring term.
By:
The largest ever cadre of ChiPy Mentorship participants meet to present their findings after 13 weeks of study with their mentors. You'll see demos and discussion for entry level projects, web development projects and data science experiments gone mad with the power of Python. Each presenter gets five minutes to tell the story of their journey and what they produced. Plus amazing prizes and announcements on how to apply for the spring term.
174 Python enthusiasts attended this meeting.
Thu, Dec 08 2016 at 06:00 PM at LaSalle Network
Using pyodbc to execute SQL queries
(20 Minutes)
By: Anish Krishnan
How to access a database using pyodbc, and how to execute basic queries through Python.
(20 Minutes)
By: Anish Krishnan
How to access a database using pyodbc, and how to execute basic queries through Python.
Python in the Classroom and at Sea
(15 Minutes)
By: Thane Richard
I was Ray's mentee during the summer of 2016. My project lets a player of Minecraft Pi 3D print an object they have built in the game. I will co-present this project with Peg Keiner, the Technology Director at GEMS World Academy in Chicago where my program was used in their elementary school classroom this Fall. I will also share some neat projects from my stint this Fall as a High School Marine Science teacher aboard the schooner Roseway during Ocean Classroom (worldoceanschool.org). I introduced students to Python and had them design and code a sensor kit with Raspberry Pi's to measure an aspect of the sailboat. The code is viewable on my github profile: https://github.com/thaneofcawdor.
(15 Minutes)
By: Thane Richard
I was Ray's mentee during the summer of 2016. My project lets a player of Minecraft Pi 3D print an object they have built in the game. I will co-present this project with Peg Keiner, the Technology Director at GEMS World Academy in Chicago where my program was used in their elementary school classroom this Fall. I will also share some neat projects from my stint this Fall as a High School Marine Science teacher aboard the schooner Roseway during Ocean Classroom (worldoceanschool.org). I introduced students to Python and had them design and code a sensor kit with Raspberry Pi's to measure an aspect of the sailboat. The code is viewable on my github profile: https://github.com/thaneofcawdor.
Smuggling Snakes in a Box: A Docker + Python Love Story
(30 Minutes)
By: Hector Rios
Experience Level: Novice
Do you yearn? Have you ever tried to volunteer at a project but had an extremely difficult time trying to get everyone the right development environment? Do you ever work with a project that works in your computer but not in a server? Do you have a different dependency versions? (btw, that's kinda bad practice but don't fret, we gotchu) Yearn no more! With Docker, these things can be a thing of the past. Join in a brief, live coding session that will show you how to build a simple Bottle app and put it into a Docker container.
(30 Minutes)
By: Hector Rios
Experience Level: Novice
Do you yearn? Have you ever tried to volunteer at a project but had an extremely difficult time trying to get everyone the right development environment? Do you ever work with a project that works in your computer but not in a server? Do you have a different dependency versions? (btw, that's kinda bad practice but don't fret, we gotchu) Yearn no more! With Docker, these things can be a thing of the past. Join in a brief, live coding session that will show you how to build a simple Bottle app and put it into a Docker container.
158 Python enthusiasts attended this meeting.