Day 1, R0 09:20–10:20
有人說,資料是新時代的石油;那麼,人工智慧 (AI) 就是新時代的電力,未來將不會有任何現代產業與 AI 無關。
問題在於 AI 技術的引入會面臨兩大挑戰,挑戰一,AI 是解決特定問題的技術:同樣是深度學習模型,要解決什麼問題,能解決什麼問題,能解到什麼程度,產生多少價值,在每家公司都不一樣,多元性及客製化程度遠比導入 ERP (企業資源計畫)、 CRM (客戶關係管理) 系統高得太多。例如,同樣是 AOI (自動光學檢測) 技術,在 A 公司做來檢測電路板的瑕疵,在 B 公司檢測織物的瑕疵,在 C 公司檢測玻璃的瑕疵,以高標準來要求的話,絕對不是調整參數就好。因此,未來的五年甚至更久的時間內,很難期待會有套裝系統可以直接購入及進行簡單客製化,符合各產業、各公司、各種問題的期待。
挑戰二,AI 並沒有辦法 plug & play (即插即用):目前的 AI 皆由機器學習模型來驅動,而機器學習必須要有大量資料來訓練。若公司內原本並沒有蒐集某個想要解決的問題的資料,或是資料蒐集時間不夠長,任你找到絕世高手或買到厲害的系統也沒有用。例如,若要進行未來半年的某產品銷量預測,通常需要該產品或同類型產品及競品在過去三年或五年以上資料,以及搭配的各式環境因素、客戶訂單資料等等。若是沒有這些資料準備好,AI 系統就是不能動,沒有油就沒有辦法發電的道理。
幸運的是,這一波 (也是人類史上的第三波) 的 AI 浪潮伴隨著「人工智慧民主化 (AI democratization)」的趨勢,最重要的概念是,AI 技術不應該只被某些跨國企業所壟斷,應該讓所有需要的人都有機會參與及使用。具體的作法包含各種深度學習開發工具及模型的開放源碼,以及各式最新核心技術的分享等等。
我個人所看到的是機會,因為這個 AI 民主化趨勢,AI 技術發展在各領域所帶來的機會無窮無盡,是習慣等待國外大廠解決方案的我們應該把握的。
當然,目前普遍遇到的挑戰是 AI 人才的缺乏,台灣人工智慧學校為此而成立。希望很快地讓「找不到人才」不再成為企業發展人工智慧的障礙,同時建立「自己的問題自己解決」的文化,打破被技術殖民的慣性,重建社會自信。
台灣人工智慧學校將以最好的師資及與產學界的密切合作,進行人工智慧技術人才的密集培訓。讓不同專業領域的學員都能如虎添翼,以人工智慧加上原本的領域知識,具備協助各企業解決問題,以及帶領人工智慧團隊的
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https://www.youtube.com/watch?v=01EJ-eH1RN0
PyCon Taiwan 2023|Talk 演講|Day 1, R0 13:05–13:35
? 說明 Description ?
With the release of Python 3.11 in October 2022, PEP 654 "Exception Groups and except" was accepted, and asyncio.TaskGroup() was added. This enhancement of exception and cancellation handling has allowed asyncio to evolve more flexibly, addressing the existing issues with asyncio APIs, such as insufficient cancellation and exception handling in asyncio.gather.
In this talk, I would like to discuss the problems of existing asyncio APIs and how the newly introduced asyncio.TaskGroup() solves these issues. Attendees will learn about the improved way of handling exceptions and cancellations using asyncio.TaskGroup(), enabling them to write more efficient and robust asynchronous code with Python 3.11.
? 講者介紹 About Speaker - Junya Fukuda ?
Develops "LOVOT", a family-like robot that promotes the ability to love, at GROOVE X, Inc. He has spoken at PyCon JP, DjangoCongress JP, EuroPython, and other events. As a community activity, he participates in the management of GeekLab Nagano. Co-author of "Python Practical Recipes (2022 Gijutsu Hyoron Co., Ltd.)". Translation of "Expert Python Programming - Fourth Edition". Likes beer, camping, and asyncio.
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https://www.youtube.com/watch?v=h8VEyMq54po
Day 1, R1 11:25–12:10
我們每天下意識的不斷評估周圍物體的穩定性、摩擦力、重量,從而預測它們在施力與翻滾時如何移動。
這些心智處理過程,是否可以透過 Python 搭配物理引擎與增強學習技術來建模與重現?
希望分享給大家我們進行實驗時用到的工具與實驗流程。
The speaker did not upload his slides.
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https://www.youtube.com/watch?v=gyppQKBsq2Q
PyCon APAC 2022|一般演講 Talks|國泰金控 Cathay Financial Holdings / 美光科技 Micron 冠名贊助
✏️ 共筆 Note:https://hackmd.io/@pycontw/HkqMv6QJi
?? Slido:https://app.sli.do/event/hVZmGa9aoAE4dTSpjVucmj
? 語言 Language:英文 English
? 層級 Level:入門 Novice
? 分類 Category:社群 Community
? 摘要 Abstract ?
If you are interested in initiating and organizing a community, you may be interested in this talk. For instance, why are some people volunteering to run a community conference like PyCon? One of the reason is "because it is fun". This talk will show you what's the fun and how to create the fun.
? 簡介 Description ?
Emergence is commonly seen in the nature and humanity.
For example, the stock market. The basic elements of social systems are human beings, and the mutual social bonds of human beings in the social system a.k.a. the stock market in our example, perpetually changes in the sense of the ongoing reconfiguration of the structure of the stock market. The stock market is the emergence of human beings in the end.
Any kind of community is also the emergence of the human beings, including the community to organize a community conference.
I have volunteered to organize a regional PyCon, PyCon Taiwan, for years. I observed some "small" and "big" emergences arising from the community, including the organizing team and general participants.
Let me talk about what I have seen and how we may initiate the emergence of a community.
? 關於講者 About Speaker - Taihsiang Ho (tai271828) ?
FLOSS contributor. Scientific computing amateur. Climber, pianist and cellist.
#pycontw #pyconapac2022 #python #community #pycon
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https://www.youtube.com/watch?v=Oc-mc5peNFk
Speaker: Muyueh Lee
http://blog.muyueh.com/real-time-visualization-with-python-and-d3-js/
Pyhton has great power in scrapping and analyzing data, and D3.js is a great tool for building visual interface. In the first part of the talk, I will demonstrate how to set up D3.js as an interactive layer on top of Python. In the second part of the talk, I will show what it can achieve, by using the "Taiwan Vegetable Auction" dataset (past 10 years transaction data of 127 kinds of vegetable, 1GB).
The dataset is too large for human to see through, a machine learning algorithm will be able to fit a regression model on the dataset, but it can't make sense of it. For example, in the following graph:
You can see the average price of green onion in different markets for the past 20 years, the fluctuation between different markets are similar, yet since 2010, there is a perfectly horizontal blue line: while price in the other markets have changes, price in "Taitung" has remained exactly the same, suggesting a possible case of monopoly. One can then asks the system to detect other cases of monopoly. This process of exploratory data analysis can only be possible with both machine and human.
From a technical perspective, this talk can benefit front-end developer/data scientist to set up such a system. Yet a more profound value of the talk will be to explore how machine and human can work together.
About the speaker
Muyueh Lee (李慕約) is a programmer focus on Data Visualization, for profit and for fun, he hosts "Visualization Lighting Talk", a gathering for programmers doing data visualization work in Taiwan, and has been teaching Visualization in the graduate school of Journalism at National Taiwan University, in the DataScience Program by CfT and SYSTEX, and held various workshop in Guangzhou and Hong Kong. A list of his work can be found at http://muyueh.com/1314/
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https://www.youtube.com/watch?v=Bzl-Rgmg7vQ
PyCon Taiwan 2016|一般演講 Talks
? 摘要 Abstract ?
Time series prediction has become one of the most popular field for applying in the real world. Because there are various models to forecasting the future data, how to choose a suitable model has become a significant issue for every companies who want to join the data driven trend. In this talk, we are going to share our experience and result of the implementation of time series forecasting models. The topic will include the following points:
1. How to choose a suitable model for variety datasets,
2. Why did we choose the current models (ARIMA+SVR, SdA),
3. How to implement the models on python,
4. What problems did we face when we are implementing the model.
? 關於講者 About Speaker - 古宣佑 Hsuanyo ?
目前於 Soocii 任職後端工程師,對機器學習演算法有興趣,工作之餘,會拿工作上面臨的問題,當作練習的題目。之前曾經接觸過時間序列預測的模型開發,在學時期則是專注於自然語言處理 (Sentiment Analysis) 的相關研究。
? 關於講者 About Speaker - Trudie ?
目前就讀於台灣大學資訊管理碩士,研究推薦系統與社群網絡,於物聯網分析公司擔任資料分析師,興趣在於開發資料分析應用。
#python #pycontw #pycontw2016
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https://www.youtube.com/watch?v=ivkrU4n_ZRg