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On June 10, join 150+ developers at SF Python's meetup on Zoom on at 7:00p PDT
The theme for this evening is data. You will have an opportunity to interact with others via slack, ask speakers questions and make annoucements. CoC will be enforced - https://sfpythonmeetup.com/coc
If you have other ideas on how to make our virtual meetings better, please write SF Python founder Grace
Physical isolation doesn't mean social isolation, let's connect with 150+ Pythonistas in SF Bay Area and beyond on Zoom!
1. Disrupting the Thesaurus with Data Science - Ben Aaron
###Short talk(~10 mins + Q&A)
2. Primer on Prefect - Raul Maldonado
Some have compared "Perfect" with Airflow, learn more about what Prefect is, and what potential it may have in the Workflow Data space in Python.
3. altair_recipes: a Python package to generate essential statistical graphics for the web - Antonio Piccolboni
altair_recipes is a high level statistical graphics package for Python built on top of altair and vega which produces classic types of statistical graphics in a web-enabled, interactive form. If you need access to a collection of classic, effective data displays in one line of code, this package is an answer. There is one more thing: this package contains the "magic" function autoplot which will pick an appropriate statistical graphics for your data! It's not really magic, just the implementation of heuristics learned over three decades (!) of visualization.
Antonio is an experienced data scientist with industrial and academic backgrounds. Most recent work on big data packages for R (rmr2, plyrmr, tidyr.big), R developer tools (quickcheck), information filtering (rightload), A/B testing, web ranking. Cited 7000+ times in the scientific literature for work in bioinformatics and computational learning.
###Main talk (30 mins)
DIY data science using COVID data sources - Nitin Borwankar
The Covid pandemic has seen many different models based on different sources of data. This talk outlines how you can use publicly available data to analyse and visualize trends using different models using Jupyter Notebooks and Postgres with the Madlib extension that allows doing machine learning in the database.
(If additional time available) A Bayesian model to predict R0 the basic reproduction number, a measure of how fast the virus is spreading, will also be demonstrated with visualization for each US state and pointers on how to apply it to other data sources. This Bayesian approach is due to Kevin Systrom ex CEO of Instagram.
Nitin Borwankar is the author of Learn Data Science http://learnds.com and the founder of Numericc, a startup applying data science to software engineering.
##AGENDA for virtual meeting
7:00p - Welcome, introduce yourself on slack
7:10p - Announcements, lightning talks, main talk
8:30p - Surprise!
9:00p - Hard stop
This event is produced by:
SF Python, a volunteers-run organization aiming to foster the Python Community in the Bay Area. Please save the date for PyBay2020, 5th Annual Regional Python Conference in SF this August - https://pybay.com
Video Sponsor is IBM
For over a century, IBM has led world-changing progress by uniting, empowering, and relentlessly reinventing itself and their customers. The IBM Data Science Community is the place for data scientists and developers to learn, share, and engage with their peers and industry renowned data scientists. Join the IBM Data Science Community and participate in shaping the digital future