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Neural Art - Become a Great Artist by Deep Learning Algorithm｜Mark Chang｜PyCon TW 2016
PyCon Taiwan 2016｜一般演講 Talks
? 摘要 Abstract ?
Recently, the breakthrough of artificial intelligence is achieved by the Deep Learning algorithms. By simulating the mechanism of the visual system in human, the Deep Learning algorithms can achieve the human-level precision in image recognition tasks. Also, it is possible to mimic the process of "Creating an Artwork" by deep neural networks. Given a photo A and a artwork B, this deep neural can create a new artwork with the exactly same content with photo A and same style with artworks B.
? 關於講者 About Speaker - Mark Chang ?
A Python developer and machine learning scientist in "Learning by Hacking", and he is specialized in deep learning, natural language processing and computer vision.
He is also a web engineer in g0v community and Appendectomy Project.
- Blog: http://cpmarkchang.logdown.com/
#python #pycontw #pycontw2016
Follow “PyCon Taiwan”
⭐️ Official Website: https://tw.pycon.org
⭐️ Facebook: https://www.facebook.com/pycontw
⭐️ Instagram: https://www.instagram.com/pycontw
⭐️ Twitter: https://twitter.com/PyConTW
⭐️ LinkedIn: https://www.linkedin.com/company/pycontw
⭐️ Blogger: https://pycontw.blogspot.com
...
https://www.youtube.com/watch?v=MlHNyx7fbok
? 摘要 Abstract ?
Recently, the breakthrough of artificial intelligence is achieved by the Deep Learning algorithms. By simulating the mechanism of the visual system in human, the Deep Learning algorithms can achieve the human-level precision in image recognition tasks. Also, it is possible to mimic the process of "Creating an Artwork" by deep neural networks. Given a photo A and a artwork B, this deep neural can create a new artwork with the exactly same content with photo A and same style with artworks B.
? 關於講者 About Speaker - Mark Chang ?
A Python developer and machine learning scientist in "Learning by Hacking", and he is specialized in deep learning, natural language processing and computer vision.
He is also a web engineer in g0v community and Appendectomy Project.
- Blog: http://cpmarkchang.logdown.com/
#python #pycontw #pycontw2016
Follow “PyCon Taiwan”
⭐️ Official Website: https://tw.pycon.org
⭐️ Facebook: https://www.facebook.com/pycontw
⭐️ Instagram: https://www.instagram.com/pycontw
⭐️ Twitter: https://twitter.com/PyConTW
⭐️ LinkedIn: https://www.linkedin.com/company/pycontw
⭐️ Blogger: https://pycontw.blogspot.com
...
https://www.youtube.com/watch?v=MlHNyx7fbok
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Day 2, R1 11:55–12:10
Implementing machine learning solutions at scale can be challenging. Especially, when data processing and modeling need to be deployed in distributed systems.
With its in-memory processing capabilities, Apache Spark has been all the rage for large scale data processing and analytics. Adopting Apache Spark in production become common. High-level APIs also make the learning cure of Apache Spark flatter. However, it is still not painless to move experimenting Python scripts into Apache Spark jobs in production.
An opensource project, “Koalas”, is aims to relieve the pain by implementing the pandas DataFrame API on top of Apache Spark. We will start by briefly introducing Koalas. Then, the main focus is about how to use Koalas to make machine learning projects running with Spark, including comparing the difference between Apache Spark, Pandas, and Koalas. Then, through a few examples,we will demonstrate how to develop on a single codebase that works both with pandas and with Spark.
Slides: https://docs.google.com/presentation/d/1Q4cX-p0U6jvVAm2dxyUslKsLA6R00C2XeIddJGwFH4U/edit?usp=sharing
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https://www.youtube.com/watch?v=r6MnlzdW-YY
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Day 3, R2 10:50–11:20
The SQL client is ubiquitous and impossible for developers not to have one in their toolbag. However potentially there is a unforeseen situation that the developers are forbid to use SQL client to access the cloud/on-premise SQL DB. This proposal primarily addresses the issue of such scenario and provides a solution based on the hacker's mindset. In this proposal, the author will show how he tackles this pain point in his workplace, by creating a universal SQL client CLI that allows him to connect to the SQL DB in his DB cluster, hence extends this project to other SQL DB using the API standardization in PEP 249. Apart from integrating all the SQL connectors, the author also implemented standardize hotkey for all the SQL DB, by studying the internal core of the SQL standards, and retrieving SQL metadata using pure SQL queries through the hotkeys.
Slides not uploaded by the speaker.
Speaker: Ing Wei Tang
Ing Wei is the chair for PyCon MY 2019, the co-chair of PyCon MY 2018, and vice president of MyPOP. He has spoken in various PyCons, particularly in PyCon APAC 2018, as well as involving in PyCon communities actively in Malaysia.
He uses python a lot in his daily work, especially coding the automation process and flow. During his past time, he likes to experience and perform hacking different things on operating system level.
Apart from programming language, he can also speak 5 different types of languages concurrently in one sentence. Please ask for demo if time permits.
...
https://www.youtube.com/watch?v=3tP3UHfv9rs
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R1 DA
r1-day1-05-network-security-and-analysis
Speaker: Lee Yang Peng
I developed and evaluated Analytics, a tool that analyses packet data to learn information about network protocol formats. Analytics attempts to discover constants and enumeration fields among packet data, while providing visualization to aid analysts. My experiments on fixed length protocol headers show that the heuristics implemented for Analytics in detecting constants and enumeration fields are mostly accurate. It has an average accuracy in detecting constants of 76.8% and an average accuracy in detecting enumeration fields of 88.6%. As Analytics consists of heuristics to detect the targeted fields in network traces, it can also be applied onto proprietary or unknown protocols.
From my talk, audience can learn about network security and its significance. Poor network security can result in vulnerabilities in an organization, which may result in commercial espionage, the leakage of company secrets, or the control of computers connected to the network to perform illegal activities. Audience can also benefit from my talk by learning about Deep Packet Inspection, a common process used in large organizations to maintain network security and prevent the transfer or malicious data through a network. Experts in the field can appreciate the tool, 'Analytics', that demonstrates the use of Python in garnering information about unknown network protocol formats.
About the speaker
I'm a 16 year old student from Dunman High School
組織/公司 Dunman High School
頭銜 Student
...
https://www.youtube.com/watch?v=7qsixKitI18
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Day 1, 10:05-10:35
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如何效率地從龐大的非結構化文字資料，萃取重要的結構化資訊是大數據分析的基礎。本次演講以結合金融業務與精準醫療為出發點，藉由智能理賠(醫囑分析)作為案例，探討如何透過自然語言處理技術，將瑣碎且重複性極高的作業流程逐步化繁為簡。 就技術而言，此乃自然語言處理領域中的命名實體識別任務。在現今預訓練與微調兩階段模式盛行之下，以Transformers為基調的模型在此任務已達一定水準。但是，當資料具有多含義實體(同一實體具有兩個以上含義，e.g. 急診日期通常也隱含了入院日期的含義)時，模型僅僅具備七成至八成的辨識水準，而多含義實體在醫囑資料或醫療文獻尤為常見，因此，我提出一種深度學習應用框架-自問自答，同時處理單含義與多含義實體。 以一篇醫囑來說，模型自問多個問題(e.g. 請找出入院日期。)，根據這些問題，回答相應的實體答案。而多含義實體的各個意義，可被不同的獨立問題所切分開來，因而巧妙解決多含義實體問題。 演講過程中，我會以知名的Python套件(Transformers)與Pytorch為實作核心，輔以介紹，透過Transformers套件可快速套用許多預訓練模型，並實現在自身資料集裡。最後，搭配實際展示引導聽眾了解整個問題與解法的脈絡。
Description
使用的第三方工具：
transformers 為自然語言處理領域中熱門的Python套件，提供許多方便好用的API，且提供完整tutorial與免費pretrained model資源。
seqeval 為處理序列框架的常見評估工具。
Slides not uploaded by the speaker.
HackMD: https://hackmd.io/@pycontw/2021/%2F%40pycontw%2FHkTtQkYfF
Speaker: 江侑倫
NLP Engineer at CTBC bank
...
https://www.youtube.com/watch?v=yxczI4BpT8Y
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Day 2, R1 11:45–12:15
深度學習技術快速進步, 我們能訓練神經網路來控制實體機器人, 但訓練過程會發生各種突發狀況, 在物理安全與經濟狀況考慮下, 先在模擬環境完成訓練再轉移到真實機器人是一種解決方法。 但是模擬環境與真實環境有許多物理落差, 速度或摩擦力等各種物理因素, 都會導致訓練好的模型轉移到真實環境的效能低落。 去年 Google Brain 透過對物理引擎的模擬過程進行參數化與隨機擾動來解決問題, 我們也透過同樣方法完成二輪平衡車控制模型的虛實轉換, 這場分享將會介紹我們如何從無到有, 在物理引擎建立 車體3D模型, 並用 Python 參數化各種物理量, 最後展示完成的機器人可以做為訓練環境, 用來訓練神經網路控制模型。
Slides not uploaded by the speaker.
Speaker: Jiawei Chen
MLDM Monday與 Kaohsiung Python社群 Co-organizer, 目前在學術單位擔任研究人員，熱衷於研究機器學習相關技術，喜歡分享相關技術，並應用在實務工作上。
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https://www.youtube.com/watch?v=yAU33QgDLzw
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PyCon APAC 2022 | 贊助夥伴 Sponsors
? 白金級贊助 Platinum Sponsors ?
國泰金控 Cathay Financial Holdings
美光科技 Micron / @MicronTechnology
? 銀級贊助 Silver Sponsors ?
沛星互動科技 Appier
Berry AI / @Berry AI
Dcard / @Dcard
玉山銀行 E.SUN Commercial Bank
資廚 iCHEF
KKCompany / @KKCompany
Pinkoi / @Pinkoi
Reuven Lerner, Python Training / @Reuven Lerner
永豐金證券 SinoPac Securities / @永豐金證券
? 銅級贊助 Bronze Sponsors ?
中國信託銀行 CTBC Bank / @CTBC Bank
Elastic / @Elastic
聖學科技股份有限公司 GoFreight / @GoFreight
塔圖科技股份有限公司 Tagtoo
? 特別贊助 Special Sponship ?
HackMD / @HackMD
天瓏書局
咪卡創意 Micare Production / @Micare Production咪卡創意
Python Software Foundation (PSF) / @Python Software Foundation
Gather
百變怪貼紙 StickerHD / @StickerHD 百變怪貼紙
Packt / @Packt Video
LOGOless
LaLoKa Labs
❤️ 特別感謝 Special Thanks ❤️
MOPCON / @MOPCON
Taichung.py / @Python TaichungPy
Kiwi PyCon / @Kiwi PyCon
PyCon HK / @PyCON Hong Kong
Python PH / @PythonPH
PyCon JP / @PyCon JP
PyCon MY / @PyCon MY
#python #pycontw #pyconapac2022
Follow “PyCon Taiwan”
⭐️ Official Website: https://tw.pycon.org
⭐️ Facebook: https://www.facebook.com/pycontw
⭐️ Instagram: https://www.instagram.com/pycontw
⭐️ Twitter: https://twitter.com/PyConTW
⭐️ LinkedIn: https://www.linkedin.com/company/pycontw
⭐️ Blogger: https://pycontw.blogspot.com
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https://www.youtube.com/watch?v=zs4eVnzhon8
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[PYCO
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Ami is a data scientist employed for the past five years at Final, a financial algorithms company in Israel. Before that, as part of Ph.D studies, he lectured at Tel-Aviv University. Between 2000 and 2005, he worked at IBM's Haifa Research Labs as a researcher in the field of large distributed storage systems.
In 2010 he received a Ph.D in Electrical Engineering from Tel Aviv University, in the field of financial information theory. His bachelor's and master's are from Tel Aviv University too.
Ami uses Python and C++ for data analysis. He contributed to various open source projects, and is the author of a libstd C++ extension shipped with g++ (pb_ds: policy-based data structures).
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https://www.youtube.com/watch?v=pFbjBzhrUpY
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REACT
reactive-programming-in-python-keith
PyCon Taiwan 2016｜一般演講 Talks
? 摘要 Abstract ?
In relation to Internet of Things, micro services, and big data, a developer is easily being expected to handle the stream of data flow. A growing fantasy of Reactive programming is being told that a paradigm can help people to face these challenges in theory and practice and to make life easier. Is it True? Or, does it SCALE?
Join the quest to to discover reactive design and data workflow implemented in Python. We’ll inspect their features and use cases of reactive programming, to name a few, Python built-in, PyFunctional, RxPy, Flexx, async and await (and asyncio), Promise, … etc., study their best practices, and discover the elegant part compared with commonly seen sequential chaining. We also want to know when it may complicate your code.
? 關於講者 About Speaker - Keith Yang ?
最近覺得邊騎室內腳踏車邊用電腦，離開臉書與 IG 的精神（神經？）生活很不賴。讓這隻小白鼠從大眾心理控制實驗學裡喘了一小口氣。
Recently he enjoys skateboard commute, still coffee-achemy, and indoor cycle while programming or gaming, an awesome mind vocation of leaving FB and IG. Keith is the founder and co-organizer of Taipei.py, largest Python user group in Taiwan, a Lead Software Engineer at iCHEF, and was Chairperson of PyCon APAC 2015. His work mostly focuses on web/backend/cloud services since 2006, and he hands on kernel tools of virtualization on hypervisors in 2016.
#python #pycontw #pycontw2016
Follow “PyCon Taiwan”
⭐️ Official Website: https://tw.pycon.org
⭐️ Facebook: https://www.facebook.com/pycontw
⭐️ Instagram: https://www.instagram.com/pycontw
⭐️ Twitter: https://twitter.com/PyConTW
⭐️ LinkedIn: https://www.linkedin.com/company/pycontw
⭐️ Blogger: https://pycontw.blogspot.com
...
https://www.youtube.com/watch?v=Jdir84yZsVo
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這
這樣的開發環境沒問題嗎-–
Day 1, R0 13:45–14:30
如果把軟體開發比喻成音樂，開發環境就是開發者的樂器。好的開發環境會讓開發過程更順利，減少使用者需要煩惱的外務；當你專注在需要研究的課題上，便能完成更好的作品。最好的開發環境，應該讓你成為更好的開發者。
由於 Python 的根基來自 Unix 文化，它周圍的工具鏈（toolchain）也深受其「do one thing, and do it well」哲學影響，著重於創建單一功能，可與其他工具互動的元件。搭配開源社群常見的「bring your own tools」理念，Python 傳統上並沒有一個「標準」的工具搭配，而是讓大家發揮創意自由組合。這同時是優點，也是詛咒——不論你的背景為何，都可以在 Python 找到習慣的配置，但是經驗較少的人就容易犯錯，用了不適合自己，甚至根本錯誤的開發環境。
講者在這個議程將根據自己參與 Python 工具鏈專案、以及觀察、建議 Python 開發者建構環境的意見，描述常見的開發狀況、常見的組合、容易混淆的工具用法，並根據這些問題提出建議，希望讓大家能夠找到有用的資訊，建構讓自己更得心應手的開發環境。
Slides: https://speakerdeck.com/uranusjr/zhe-yang-de-kai-fa-huan-jing-mei-wen-ti-ma
...
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