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.

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.

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.

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.

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

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.

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. A demo of the hardware connectivity will be shown which includes an Atlas Scientific pH meter, digital submerged temperature probe, liquid flow meter, liquid level sensor, video camera, and an eight channel relay controlling 12V DC water and 120V AC CO2 gas solenoids, peristaltic dosing pumps, and lighting. A live python coding demo with sample scripts will show how to connect to the serial devices and control the analog and digital hardware. We will broadcast the measured data and hardware states using the Eclipse Paho MQTT python client with the IBM IoT Foundation on BlueMix or IBM MessageSight to create a dashboard using a Javascript MQTT client and Freeboard.io. Finally, we'll create a linux script which allows the attached RaspiCam to live stream a HD video to Google's Youtube Live so the whole world can see.

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.

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.