CRUG & ChiPy: The cross-over meetup of the year!
Details
CRUG and ChiPy are holding their first ever joint R and Python meetup! We've got an R talk, we've got a Python talk, we've even got R AND Python talks, and we'll host a Round table discussion about R and Python!
Door's open at 6, talks begin at 6:30 pm. Pizza and meeting space kindly provided by our event host Braintree Payments: The Simple Way to Get Paid. Closed captioning and beer generously provided by IBM. Thank you to both for making this meetup possible!
IMPORTANT NOTE: Braintree will ask for a photo ID at the door and the name must match your name on their list. Upon registration, please type in the name on your ID in the pop-up box prompt.
Below is our current lineup, and we may have a few more late additions as well. Each talk will be about 20 minutes in duration.
## Package mmap: Map Pages of Memory, by Jeff Ryan
https://cran.r-project.org/web/packages/mmap/index.html
The mmap package offers a cross-platform interface for R to information that resides on disk. As datasets grow, the finite limits of Random Access Memory constrain the ability to process larger-than-memory files efficiently. Memory mapped files ("mmap" files) leverage the operating system's demand-based paging infrastructure to move data from disk to memory as needed, and do it in a transparent and highly optimized way. This package implements a simple low-level interface to the related system calls, as well as provides a useful set of abstractions to make accessing data on disk consistent with R usage patterns. As new breakthroughs in data storage technologies crush disk read/write times, the mmap package stands to become even more valuable to analysts managing larger-than-memory data sets.
## Python EOgmaNeo Self-Driving Model Car: Powered by Raspberry Pi 3B+ and Arduino, by Yana Lustina
https://github.com/ylustina/sdc-EOgmaNeo
The program runs on the Pi, and performs all the online machine learning on the Pi's CPU. With the OgmaNeo library, there is no pre-training and no offloading to a more powerful machine. The network learns to predict the next command as you drive it. The car takes video from the camera and the steering angles as input, and uses a predictive hierarchy to predict the next desired steering angle. This greatly lowers the computational cost, as well as saves the time and work necessary for collecting data for other kinds of neural networks. Yana's ambitious work earned first place in ChiPy's competitive one-on-one Mentorship Program.
## Base R and Python Pandas, by Parfait Gasana
https://stackoverflow.com/users/1422451/parfait
This talk will compare Python Pandas and base R through import/wrangling/aggregation of XML, JSON, and SQL data. A glimpse of working with rpy2 (run R inside Python) will be offered as well. A very practical, interesting, and relevant talk to this joint meetup, Parfait will show us how both R and Python are great additions to a data professionals toolkit!
## Round-table Discussion
A panel of experienced R and Python developers answer relevant questions about programming with data from our moderator and field a few from the audience too!