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Call for Proposals - Swiss Python Summit The first Swiss Python Conference is coming up February 5th, 2016 at HSR University of Applied Sciences in Rapperswil. Thinking about attending and want to give a talk, click through to submit a talk proposal! python-summit.ch Shared by @myusuf3
Python 3.5.0 Released! No more RC's, the release of Python 3.5.0 is upon us! Click through to check out the release notes and download. python.org Shared by @myusuf3
pyNES Amazing! Capture some of that childhood nostalgia (if you are old enough) and write NES Games in Python. gutomaia.net Shared by @mgrouchy
prettyconf A extensible library for Settings and Code separation. Meant to follow the 12Factor app recommendations. github.com Shared by @myusuf3
PeachPy A Python framework for writing high-performance assembly kernels. PeachPy can directly generate ELF, MS COFF and Mach-O object files and assembly listings for Golang toolchain. github.com Shared by @myusuf3
lightfm A Python implementation of LightFM, a hybrid recommendation algorithm. github.com Shared by @mgrouchy
armada A complete solution for development, deployment, configuration and discovery of microservices. Develop good practices in making your platform more service oriented. github.com Shared by @myusuf3
videodigest This is pretty cool! Looks at a video's subtitles to determine the most important sentences in a video then creates a video of the regions where those sentences take place! Click through to the README to check out some examples. github.com Shared by @myusuf3
Pineapple Very cool. A standalone development environment on OSX for Jupyter notebooks for doing data science in Python. github.io Shared by @mgrouchy
Articles
Ball Tracking with OpenCV Always something cool coming from PyImageSearch! For the blogs 100th post the author demonstrates how you would track a coloured ball using computer vision techniques and OpenCV. pyimagesearch.com Shared by @myusuf3
Hacking the Random Walk Hypothesis Learn about the Random Walk Hypothesis, about the creation of a test suite to determine randomness and then do some experiments to determine the randomness of financial markets. turingfinance.com Shared by @mgrouchy
Using Machine Learning to Provide Recommendations Another nice tutorial over at code mentor. Very nice and detailed tutorial shows you how to use machine learning to provide in this case wine recommendations to users based on users wine review data. codementor.io Shared by @myusuf3
Analyzing 1.7 Billion Reddit Comments with Blaze and Impala If you are interested in the Blaze Ecosystem this will be very relevant to your interests. In this post the author demonstrates how to analyze Reddit comments with with Blaze and impala. The author starts from Installing dependencies and continues to preparing the data and finally the analysis. github.io Shared by @mgrouchy
