WOMEN IN DATA SCIENCE
TAIPEI CONFERENCE 2019

The Global Women in Data Science (WiDS) Conference 在 2015 年 11 月於美國史丹佛大學 (Stanford University) 成立, 是一個國際知名的科技論壇, WiDS 創立有三個目標:

• 不分性別並致力於教育發展, 期望提供所有參與者一個吸收最新研究, 技術發展以及產業趨勢的平台。

• 期望能激發學生對於資料科學各項研究領域以及應用的學習熱忱, 同時使更多女性能成為學生未來的楷模, 也讓學生能探索及了解未來資料科學相關領域的發展機會及挑戰。

• 支持及鼓勵女性參與資料科學相關領域, 不管是從事相關領域工作, 亦或是成為學術研究或教育者, 並且協助她們提昇曝光的機會, 增加與同業交流分享的機會以及協助她們的職涯發展。

WiDS 每年舉辦研討大會，邀請行業內頂尖的女性擔任演講嘉賓，並有超過150個活動由全球的WiDS大使於各地區舉辦。

WiDS Taipei Conference & Workshop

今年將是我們在臺灣舉辦的第二屆 WiDS Conference 全球區域活動，邀請了來自國內外產業界、學術界的女性研究員、工作者以及科學家來分享最新行業趨勢、職涯規劃，以及資料科學在各個領域所帶來的重大改變。每年，我們也期望與其他社群合作, 舉辦一系列資料科學相關工作坊作為論壇的暖身活動。我們希望這些活動能夠為資料科學專業人士提供一個互相交流以及分享的平台。今年我們與 Google Taiwan 合作規劃一系列免費的機器學習工作坊 (Machine Learning Crash Course Workshop)，循序漸進帶領初學者學習重要且實務的資料分析觀念，提供有興趣者一個入門以及參與的管道。

Machine learning Crash course
Concept

09:00-17:00
2019 年 3 月 17 日

早鳥票及學生票

不要錯過一年一度的 WiDS 臺北年度論壇, 註冊早鳥票還可享有早鳥優惠，早鳥票數量有限喔！

WiDS Taipei 同時提供學生優惠折購，學生票入場時需出示學生證件

Welcome Adress & Opening Remarks

Using Health Data to Drive Changes in Rural Health Care

Elvena Fong
Health Data Analytics Program Manager, The Center for Health Systems Innovation (CHSI) at Oklahoma State University

10:50 - 11:50

(R 102)

Redefining Robots & Demystify Next Generation AI Enabled Robotics

Bastiane Huang
Product Manager, Osaro

Machine learning has made it possible to shift from manually programming robots to allowing machines to learn and adapt to changes in the environment. We will discuss how AI-enabled robots are used in warehouse automation and how we can use warehouse robotics as an example for other industries such as manufacturing and food assembly. We will describe recent progress in deep reinforcement learning and imitation learning, and discuss the requirements and challenges of various industrial problems, both pipelined and end-to-end systems. Our talk also covers the technology Osaro developed to address the challenges in industrial robotics.

10:50 - 11:50

(R 103)

Measurement & Omni-Channel Marketing to Grow Social Enterprise

Sharon Chai 翟翎琇
Analytics Lead, Marketing Effectiveness, Athleta (Gap Inc.)

Why is it important to measure marketing efforts? What are the best practices and processes in theory to ensure that marketing is truly effective? How do you handle the challenges of a real-world retail environment and what are practical steps to optimize marketing spend? Sharon will share her perspective on bringing data to omni-channel marketing at Athleta, a premium fitness and lifestyle brand that is committed to igniting a community of active, healthy, confident women and girls who empower each other to reach their limitless potential. Come listen to hear how her journey from literature to data science and a growth-oriented mindset help her combine the art and science of marketing.

Lunch Break

13:00 - 14:00

(R 102)

Tactics for Empowering A Product with Artificial Intelligence

Guiguan Lin 林冠樺
Technical Project Manager, GallopWave

With the advancement of technology, we are connected to artificial intelligence in our daily lives - and indeed it will grow at a quicker pace in the near future. There are some amazing cases AI are used behind the scenes to improve user experience. However, AI is not the panacea and cannot be easily adopted. In this talk, I will share the tactics for applying AI into a product in different phases: from ideation, development, launch, to enhancement.

14:10 - 15:10

(R 102)

14:10 - 15:10

(R 103)

Hypothesis Testing With Python: True Difference or Noise?

Mosky Liu 劉依語
Python Charmer, Pinkoi

In an experiment, the averages of the control group and the experimental group are 169.61 and 169.88. Is the experimental group better than the control group? Or is the difference just due to the noise? In this talk, I will introduce statistical hypothesis testing to rule out the noise. Moreover, Python-based visualization, calculation, and simulation of various topics will be demonstrated, including α, β, effect size, sample size, inverse α (false discovery rate), and inverse β (false omission rate).

15:30 - 16:30

(R 103)