【Event】Café Philo ＠ NY // Taiwanese Data Professionals
【Topic】Conversation with Susan Sun and Luke Lin
【Time】3/30 (Fri) 7:30 PM
【Location】WeWork Times Square
【Speaker】
* Susan Sun | Freelance data scientist
* Luke Lin | Data Scientist At NYC Data Science Academy
【Introduction】
Susan works in a variety of fields, from academia to industry, corporate to nonprofit, including notable data leaders like New York Times, Google, CUNY, and DataKind. Susan holds a Masters in Statistics at Columbia University and a Bachelors in Economics at the University of Pennsylvania ,Wharton Business School. She will share her insights and experiences on freelancing as a data scientist.
Luke received his PhD degree in Math from The State University of New York at Stony Brook SUNY, Luke’s research activities concern mathematical analysis and partial differential equation. Currently, Luke is a Data Scientist At NYC Data Science Academy, focusing on R, Python and Machine Learning. He will be talking about Flask, Google API, and his Imaginary Post Big Data Era.
【Host】Hsu Yi-hsuan
【Venue】Hsin Hsiao｜Software Engineer，Founder of Startup in NY
【Coordinate】Kuang-Ting Chang, Robin Lee, Hsi-Ling Liao, Yu-Han Chen
https://www.eventbrite.com/e/conversation-with-susan-sun-and-luke-lin-tickets-44519656491
https://www.facebook.com/events/152176568942820/
Saturday, March 24, 2018
Tuesday, March 6, 2018
Code of Conduct
Organizers will enforce this code throughout the event.
TDP is dedicated to providing a harassment-free experience for everyone, regardless of gender, sexual orientation, gender identity and expression, disability, physical appearance, body size, race, or religion. We do not tolerate harassment of event participants in any form.
All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery is not appropriate for any event venue, including talks.
Be kind to others. Do not insult or put down other attendees. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate for TDP.
Attendees violating these rules may be asked to leave the event.
Thank you for helping make this a welcoming, friendly event for all.
TDP is dedicated to providing a harassment-free experience for everyone, regardless of gender, sexual orientation, gender identity and expression, disability, physical appearance, body size, race, or religion. We do not tolerate harassment of event participants in any form.
All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery is not appropriate for any event venue, including talks.
Be kind to others. Do not insult or put down other attendees. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate for TDP.
Attendees violating these rules may be asked to leave the event.
Thank you for helping make this a welcoming, friendly event for all.
2018/2/23 Event Record
Taiwanese Data Professionals (TDP) and Cafe Philo at New York are honored to invite James Powell and Robin Lee to speak about their experiences in organizing data community and working on reproducible data workflow.
James kicked off the evening by sharing his thoughts on the importance of building a community. He has been a rock star in organizing conferences and meetup groups related to Python and data science. So why building a community? Why bother volunteer? According to James, building community is about collective action -- doing something greater than what you can do with your own resources. While helping good people succeed, you are motivating them to do the same thing for others in the future. And in the long term, you are helping the community succeed. For James, building a community is truly about optimism about the society: Through collective action, we are creating the world that we envision to live in.
Robin’s talk, on the other hand, focused on reproducible, auditable, accurate, and collaborative SQL workflow. As analysts or data scientists working with data every day, a lot of us made mistakes when processing data. However, instead of blaming individuals on their personal failures, it is more important to change that mindset and examine the system to see how the system has failed. It is only through learning from mistakes and establishing a reliable, reproducible workflow that we become a better data scientist/analyst day by day. It is important to have this mindset and understand concepts such as modular code, dependency management, and executable analysis script for our everyday work. He then shared an SQL workflow example by using data for Hacker News.
James kicked off the evening by sharing his thoughts on the importance of building a community. He has been a rock star in organizing conferences and meetup groups related to Python and data science. So why building a community? Why bother volunteer? According to James, building community is about collective action -- doing something greater than what you can do with your own resources. While helping good people succeed, you are motivating them to do the same thing for others in the future. And in the long term, you are helping the community succeed. For James, building a community is truly about optimism about the society: Through collective action, we are creating the world that we envision to live in.
Robin’s talk, on the other hand, focused on reproducible, auditable, accurate, and collaborative SQL workflow. As analysts or data scientists working with data every day, a lot of us made mistakes when processing data. However, instead of blaming individuals on their personal failures, it is more important to change that mindset and examine the system to see how the system has failed. It is only through learning from mistakes and establishing a reliable, reproducible workflow that we become a better data scientist/analyst day by day. It is important to have this mindset and understand concepts such as modular code, dependency management, and executable analysis script for our everyday work. He then shared an SQL workflow example by using data for Hacker News.
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