Did you know machine learning is behind a vast of technologies that we use today? Muthoni Wanyoike, the team lead at Instadeep Kenya and an Actuarial Science graduate from Dedan Kimathi University of tech is one of the great brains behind the Women in Machine Learning and Data Science community Nairobi chapter, (WiMLDS) Kenya. "When I started the Nairobi chapter of WiMLDS, I was just starting out in Data Science at the ICT Authority's Kenya Open Data Initiative. I was really looking for a community where I would gain new skills and also connect with people with the same interest as well as those already in the industry," says Muthoni Muthoni, however, admits setting up a community was not easy. At first, they organized meetups where they would charge participants to attend sessions on data science and machine learning with an abundance of Faith that attendees would believe in their vision.
On Saturday, July 22nd Mitzi Morris and I (Michael Betancourt) will be hosting a day-long Stan workshop for the NYC Women in Machine Learning & Data Science Meetup Group. As with most of our workshops the emphasis will be on interactive exercises where everyone builds and running models in Stan. We'll start with the foundations of Bayesian inference and end all the way at fitting latent Gaussian process models. Everything for this course will be in Python and PyStan. If you're in the New York City area and want to attend then you can register at the event page.
Reshama is a freelance data scientist/statistician with skills in Python, R and SAS. She earned her M.S. in statistics from Rutgers University. She earned her M.B.A. from NYU Stern School of Business where she studied strategy, business analytics and technology management. She began her statistical career at Educational Testing Service. She then worked for over 10 years as a biostatistician in the pharmaceutical industry at various companies including PPD, Merck, Thomas Jefferson University and Pfizer, covering Phase I through Phase 4 clinical trials.
WiMLDS Paris is launching a new format: paper reading sessions. These sessions will happen at lunchtime, each 3rd Thursday of the month. The goal of these events is to take some time to discuss Machine Learning and Data Science papers that we found interesting, and take the opportunity to discover ML-passionate people in Paris. The events are limited to 30 people so discussions between attendees remain possible. This session's paper will be "Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification" (https://bit.ly/2lFtFTR),