SQLAlchemy: Beyond ORM
Before I started my new job, I thought of SQLAlchemy as "that ORM people use with Flask." Well, it is that - and more! With this talk, I want to give the audience a taste of SQLAlchemy's philosophy and capability.
1) Picking the right abstraction: SQLAlchemy's ORM and Core layers.
2) Transaction management: The Unit of Work pattern (SQLAlchemy) vs. the Active Record pattern (Django models, Rails ActiveRecord).
3) In the wild: code samples plus practical concerns like migrations.
An Introduction to the Portable Format for Analytics (PFA) and to Python-based Titus Scoring Engine
The Portable Format for Analytics (PFA) (www.dmg.org) is an emerging standard for predictive analytics that addresses some of the limitations of the Predictive Model Markup Language (PMML) and was designed for today’s big data environments, including Hadoop, Storm and Spark.
In this talk, I give an introduction to PFA, model deployment, and Titus: Open Data's Python toolkit for building, inspecting, and modifying PFA scoring engines.
Robert Grossman is the Founder and a Partner at Open Data Group, which has building predictive models over big data for its clients since 2002. He is also a Professor in the Division of Biological Sciences at the University of Chicago, where he leads a research group in bioinformatics with a focus in managing and analyzing large genomic datasets for advancing the understanding of human disease.
Meet the micro:bit
You may have heard of the BBC micro:bit - a tiny (2" x 2.5") ARM based single board computer that every 11 year old in Britain will be receiving in a few months. (And if you haven't, well, as for everything else, start with Wikipedia.) Even better, the micro:bit runs Python 3 (MicroPython, to be exact).
The Python Software Foundation is a partner in the project. (see http://ntoll.org/article/story-micropython-on-microbit for more)
The micro:bit will be released in the UK some time around February, and should be available commercially shortly after that. Even though the micro:bit has't been officially released yet, a few have made their way out the door. So I happen to have one these precious few devices in the wild.
I'd be happy to give a 30-45 minute talk about the background of the micro:bit and getting Python on it, about the teaching implications, the development done so far, and what's needed for the future, as well as the world tour that several of the devices are on. There would also be a live demo of the device.
114 Python enthusiasts attended this meeting.
Python at Nokia (by MacGregor Felix)
Python is known to be a multi-purpose and multi-paradigm programming language. Come see how the Reality Capture & Processing (RCP) group of Nokia HERE is making use of Python’s versatility. We will show you how HERE RCP uses Python’s Object Oriented constructs to represent business models in production systems. You will see how Python’s functional lambdas are used to elegantly facilitate the handling of big data. We will discuss the use of Python not only in production code but also in test code. We not only use Python for production purposes but also to build utilities. We hope to show you how we utilize Python's versatility and closeness to the operating system to build sophisticated tools for development and operational productivity. You’ll see our Test Driven development effort while building Python products and how we use Python in Behavior Driven Development to code language-agnostic acceptance tests for the evolution of software and services. We will also give you a pick at our Python packaging and distribution.
Python-fu in the GIMP
GIMP (the GNU Image Manipulation Program) is great all by itself but is even better with Python-fu. This talk demonstrates a little Python-fu to manipulate images in GIMP, with a little (slightly ugly) hacking to add external libraries.
132 Python enthusiasts attended this meeting.
Fancy genetics and simple scripts: Manipulating DNA data and becoming more proficient with Python
Our ability to read the genetic code of organisms and to use DNA sequencing to learn new biology has benefited tremendously from technological advances in the past ten years. My lab looks at how animals get colonized with specific bacteria. As we have been generating more data it has become clear that we are underutilizing the information. We are beginning to build resources to be more efficient and clever at data processing and data mining from biological samples. I'll talk a little about the science in the lab and show one of our Python projects that is functional but in its early stages. I am eager for feedback, and I think the talk will have resonance for a new motivated Python user in any field.
Factor analysis: simplifying high dimensional data sets for visualization and machine learning
For many machine learning problems, there are far more dimensions to our data than there need to be for efficient learning. Often a first step is dimensionality reduction to remove both redundancy and noise. In addition to more efficient automated learning, factor analysis allows us to visualize high dimensional data sets in our standard human-limited 2 or 3 dimensions. For demonstration, we will apply PCA on a set of questions asked of the audience to map everyone onto a 2D "personality" map - allowing us to visualize the underlying personality factors of those present. Beyond fun visualizations, these techniques are the basis of more efficient generalization in many machine learning problems.
Python-fu in the GIMP
GIMP (the GNU Image Manipulation Program) is great all by itself but is even better with Python-fu. This talk demonstrates a little Python-fu to manipulate images in GIMP.
113 Python enthusiasts attended this meeting.
ChiPy Mentorship Oct-Dec 2015
The wait is over! ChiPy's Mentorship program returns for the third time. We learned a lot from the previous two mentorship program and will do things a bit differently this time. This will be a quick overview how we are going to conduct the ChiPy's Python mentorship program.
Why You Can't Sit With Us - Understanding Network Analysis in Python With Mean Girls
Network analysis is a handy tool used to understand group dynamics, provide product recommendations, and prevent homicides (and other things). This talk will introduce the theory behind network analysis and showcase the flexibility of Python's NetworkX library. No knowledge of network analysis (or Mean Girls) is needed, but basic knowledge of Python and the iPython Notebook, will be helpful.
I gave this talk last month in Columbus OH at PyOhio 2015.
uWSGI is a very popular software package, but most Python programmers just connect it to nginx, and leave it at that. I'll be exploring some of the more advanced features of uWSGI, and how they can make your life easier.
Setting Up Machine learning with anaconda
5 min What is anaconda and how do i use it
5 min What is ipython
10 min Why machine learning is fun and how to do easy classification tasks
114 Python enthusiasts attended this meeting.
Automating a fishtank with python and IoT sensors
Fish tanks are simple enough that even a child can maintain them. I don't have children yet to maintain my tank, but luckily my very patient wife has allowed me to explore over engineering a solution.
In this talk we'll explore how python scripts running on a Raspberry Pi can be used to measure and control many aspects of maintaining a fish tank or any number of IOT applications.
Data Games in Python
C. S. Schroeder
There has been recent work on the taxonomy of games which are based, one way or another, on real world data. Typically these games help people learn that data or how to cope with it. The traditional examples are simulation games (flight, driving, etc.), while other games incorporate data in such a way that it is beneficial to learn the real world data in the game play (trivia). These types of data-games commonly have a domain specific focus. We intend to explore the possibility of interactive games which help people to learn data analysis, in general, implementing some such games in python using web2py and Scipy.
Keep calm and conda install
Jonathan J. Helmus
Conda is a cross platform, package management system widely used in the scientific and data science Python communities. Although designed for Python packages, conda can be used to package and distribute software written in any language. This talk will cover how to use conda to install and manage scientific packages as well as how conda can be used to create isolated Python environment similar to virtualenv. Conda’s use within the Anaconda and Miniconda Python distributions will be discussed as an easy method for obtaining a full featured SciPy stack. Instructions on building packages with conda and hosting them on Anaconda.org will be covered briefly.
142 Python enthusiasts attended this meeting.