The World After Tomorrow|唐鳳 Audrey Tang (au)|主題演講 Keynotes|PyCon TW 2016
PyCon Taiwan 2016|主題演講 Keynotes
? 說明 Description ? (Talk description can be found on the collaboration note)
? 關於講者 About Speaker - Audrey Tang (au) ? Audrey Tang, a civic hacker who grew up among Tiananmen exiles, is known for revitalizing the computer languages Perl and Haskell, as well as building the online spreadsheet system EtherCalc in collaboration with Dan Bricklin. In the public sector, Audrey serves on Taiwan national development council’s open data committee and K-12 curriculum committee; and led the country’s first e-Rulemaking project. In the private sector, Audrey works as a consultant with Apple on computational linguistics, with Oxford University Press on crowd lexicography, and with Socialtext on social interaction design. In the third sector, Audrey actively contributes to Taiwan’s g0v (“gov-zero”), a vibrant community focusing on creating tools for the civil society, with the call to “fork the government”.
Speaker: Scott Tsai
Target Audience: Developers that use both C/C++ and Python
Python is the scripting language of choice for GDB but debugger scripting and programmatic debugging is underutilized in general because not enough developers are both GDB power users and familiar with Python. This talk aims to remedy that.
About the speaker
Device driver, firmware, system software developer. Open source contributor, Linux enthusiast. Worked in several Taiwanese consumer electronics companies, a big multinational corporation and a Silicon Valley startup.
個人網頁連結 http://scottt.tw/
Twitter @scottttw
組織/公司 Awit Systems
頭銜 Software Developer
https://tw.pycon.org/2015apac/zh/program/104
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https://www.youtube.com/watch?v=oAYbt2PsKng
Serverless software design/architecture is fast becoming the future of cloud computing. Yet, it’s still a confusing concept for a lot of developers [just like Docker. Sorry container enthusiasts].
This talk introduces the concept of serverless architecture to the audience, from the ground up. And then runs them through the process of how exactly would the architecture look like, how the deployment happens, and how it boosts developer productivity.
All the above would be done by actually running the audience through a live example of spinning up a light-weight serverless app (in Python, obviously) for better understanding of the concept.
PyCon Taiwan 2017 official: https://tw.pycon.org/2017/
PyCon Taiwan 2017 Facebook Fan Page: https://www.facebook.com/pycontw/
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https://www.youtube.com/watch?v=9JaBrT_5eC8
marr is a research assistant at Center for GIS, RCHSS, Academia Sinica. His interests include topics on open source, web technology, and programmer productivity. Specifically he loves spending time on Plone CMS and Pyramid framework. When not working with computers, he loves rock music. Favorite bands are Beatles, Led Zeppelin, Smiths.
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https://www.youtube.com/watch?v=IyrypwQbLAQ
Day 2, 10:35-11:20
Abstract
Nowadays data is the key to solving challenges in most of the fields say astronomy, applied maths, health care, or even sports. Data is everywhere and it is super beneficial to leverage these data to build models for making sense out of these data and tell stories. The field of sports science, especially football (soccer), is enriched by data analysis that makes us understand the game better and predict outcomes. Many people want to delve deep into football (soccer) data analysis and get their hands dirty. This talk is to help them do so by pedagogically introducing them to the introductory analytical methodologies to overcome the initial barriers of the field and start working with football data analyses and visualizations.
Description
This talk introduces the following concepts on football data analysis:
I will start my talk addressing how to get open access football event data using the statsbomb API using Python,
The next thing I will talk about is drawing a football pitch using the mplsoccer Python module, so that we can start making most of our football data visualizations on this pitch,
I will then talk about simple data visualizations like drawing shot maps, pass maps and their corresponding heat maps,
Next I will teach how to visualize a pass network on this pitch of a particular team during a particular game. We will further advance our knowledge by analyzing this pass network using the NetworkX python module that is usually used in complex network analysis in mathematics. We will learn how to calculate pass degree distributions of each player, find out which player was the most central in that pass network by calculating "centrality" of each player node, and so on,
After that, I will teach how to implement computational geometric concepts like Convex Hulls, Voronoi diagrams and Delaunay triangulations using the Python package scipy.spatial and mplsoccer on open access football tracking data so that we can analyze how many passes were available to a player at a particular instance of a game, or how a group of players broke down space on the pitch at a particular instance, etc., and
Finally I will talk about how to analyze Expected Goals (xG) using open data from statsbomb.
I will end my talk guiding the audience to the references I used for starting with football (soccer) data analysis.
One use-case for soccer data analysis is, for example, using network analysis to find out the central player from a particular team who has been performing constantly in last few matches. This player can be considered as one of the backbones for that team and are recommended to be deployed in future games.
Slides not uploaded by the speaker.
HackMD: https://hackmd.io/@pycontw/2021/%2F%40pycontw%2FBkElAGqft
Speaker: I
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https://www.youtube.com/watch?v=KBWXAWtwpcM
Day 2, 14:30–15:00
For the last year, I have been interning at CyCraft AI Lab, the leading cybersecurity firm in Taiwan. My team had to process numerous cybersecurity articles and turn them to actionable information. Due to time pressure to respond to cyber attacks, we constructed a NLP system to tackle this problem.
In the project, I construct the whole data processing pipeline to turn the articles into intelligence
1.Crawling the largest Chinese security website
2. Classifying articles to help security team quickly identify articles related to their daily missions.
3. Setting up the recommendation system of prevalent attack methods to help security analyst quickly realize the articles’ theme.
4.Recognizing attack technique in articles and labeling with MITRE ATT&CK technique
Our system has achieved 95% accuracy on our collected dataset. I will share our solutions to problems we met during the process and how I balance between intern and high school life.
Slides: https://docs.google.com/presentation/d/1wk8Hzw6fvqDemKvF2TO2W5Ot04I9iQ_giaIgShnmV9k/edit?usp=sharing
Speaker: Chia-En Tsai
Taipei First Girls Highschool Student
Artificial Intelligence club President
Intern in CyCraft AI Lab
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https://www.youtube.com/watch?v=iNfnpiqvUmE
Speaker: Poren Chiang
Holding a conference needs continuous efforts, especially when you're in charge of all those administration stuff. Simple solutions could end up with management death spiral, while complex systems like Redmine would be an overkill. Roboconf is the home-made solution we've brought up: a conference operation site built upon Django, with issue tracking, document organizing, notifications, and staff management all in one place. In this session, I'll describe situations we faced when organizing SITCON 2013, how Roboconf got itself implemented, what difference it has made throughout the process, and crazy stuff other folks at SITCON built around this system.
About the speaker
Law student at NTU, Administration Lead at SITCON '13/'14, open source advocate.
RSChiang,目前就讀於臺灣大學法律學系,在 SITCON 2013、2014 擔任行政組長;原先是個拿人工智慧做研究的普通高中生,去年暑假的某天突然轉職成鍵盤法律人。目前嘗試在學校推廣開源概念,大概是為了不辜負爺爺的名聲吧。
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https://www.youtube.com/watch?v=X755DmpkpbU