How to develop ML APIs with Python from Online Learning Dataset – PyCon Taiwan 2020
Day 2, 10:30–12:00
Recently, Python engineers have more opportunities to work with data scientists than before. At the same time, they are often faced with the research-oriented code written by researchers or data scientists. In order to integrate this code with systems such as APIs, python engineers need to additionally write the code or refactor it, and make them work on the server.
This tutorial will provide chances to experience the whole process from analysis to API development by using python. In more detail, this tutorial covers the gap between the research-oriented code and production code of machine learning APIs. What is the gap between them? How it can be implemented based on real-world python code? How can the code validate whether the dataset is correct? How can machine learning models be continuously inspected? Audiences can earn the answers to these questions from this tutorial.
Jesse is a software engineer working at an EdTech company in Tokyo. He has been developing a recommender engine which can optimize appropriate learning materials according to learner's abilities. Prior to this, he used to research the relationships between online learning behaviors and learning outcomes at the UCL Institute of Education (IOE) in the UK. His interest is in how to bridge the gap between data science and engineering. ... https://www.youtube.com/watch?v=GdKU3p2azMQ
Speaker: Jessica McKellar
About the speaker
Jessica McKellar is an entrepreneur, software engineer, and open source developer from Cambridge, Massachusetts, USA. She is a Director for the Python Software Foundation and an organizer for the largest Python user group in the world. With that group she runs the Boston Python Workshop -- an introductory programming pipeline that has brought hundreds of women into the local Python community and is being replicated in cities across the US. Jessica is a veteran open source contributor and a maintainer for several open source projects, including OpenHatch and the Twisted event-driven networking engine; she wrote a chapter on Twisted for The Architecture of Open Source Applications Volume II and the second edition of O’Reilly’s Twisted Networking Essentials.
In a PyCon US 2014 keynote, Jessica McKellar outlined the programming-education problem that exists in US high schools, but she also highlighted some steps the community could take to help fix it. Besides, the Python Software Foundation is ready to help, including looking to fund grant proposals for Python-education-related projects. Here's her challenge for the community: by next year's PyCon, we would like to see every folk does one thing to further the cause of the next generation of Python programmers.
...
https://www.youtube.com/watch?v=eGwSC6UnYTg
PyCon Taiwan 2023|Talk 演講|Day 2, R2 13:45–14:15
? 說明 Description ?
[Streamlit](https://streamlit.io/) is a popular framework for interactive web-based data apps in Python. However, there are some cases where users want to run their apps offline or without sending sensitive data to remote servers. To address these concerns, we introduce '[stlite](https://github.com/whitphx/stlite)': a WebAssembly port of Streamlit. It provides offline capability, data privacy, scalability, and multi-platform portability including desktop app packaging, while preserving Streamlit's original features, such as Python productivity and its rich ecosystem.
In this talk, we will discuss the benefits of stlite and demonstrate how to build and deploy stlite applications in a variety of ways, using ML/CV examples.
We will also look at its internals from a technical point of view, which may inspire you with ideas on how to make use of Pyodide and how to transform Python frameworks for the Pyodide/Wasm runtime.
You can try out stlite online: https://edit.share.stlite.net/
? 投影片 Slides:https://slides.com/whitphx/streamlit-meets-webassembly-stlite
? 講者介紹 About Speaker - Yuichiro Tachibana ?
Yuichiro works as a professional software developer and also loves contributing to OSS projects.
As a Pythonista, he has participated in various projects including web development, multimedia streaming, data management, computer vision, and machine learning.
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R2 DAY2-04 Marsface Project: Detecting Pseudo-artificial Structures on Mars
Speaker: Hideki Tanaka
The discovery of "Face on Mars" by NASA in 1976 has attracted widespread popular and scientific interest over the past few decades. In this project, we apply various object detection techniques, such as conventional haar-like feature based methods and state-of-the-art deep learning methods, in order to detect such pseudo-artificial structures on Mars and other planets. The scientific Python ecosystem plays a crucial role in the exploration.
About the speaker
Hideki Tanaka is a PyData.Tokyo organizer, optical design engineer, photographer based in Tokyo. He is a machine learning and deep learning enthusiast who is addicted to data science competitions.
個人網頁連結 https://www.facebook.com/HidekiPhoto
Twitter @atelierhide
組織/公司 PyData.Tokyo
頭銜 Organizer
https://tw.pycon.org/2015apac/zh/program/71
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https://www.youtube.com/watch?v=XsinyMyoZPU
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/SyWp86XJo
?? Slido:https://app.sli.do/event/9SZY8fXP6EyYUYKY5kCaTQ
? 語言 Language:英文 English
? 層級 Level:中階 Intermediate
? 分類 Category:Python 核心 Python Core
? 摘要 Abstract ?
In learning Python, everyone learns `if` statements, `for` statements, and function definitions. At that time, you will also learn that `if` and `for` lines must be followed by a colon and that the following line must be indented (because SyntaxError will be raised). So why are these colons and indentations necessary? It is because Python is designed to be so[1][2], but a deep dive into "statements" in the Python Language Reference led me to an explanation that makes sense to me. In this talk, I will take you a tour of the syntax definition, expressed concisely and without omissions in PEG (Parsing Expression Grammar).
[1] https://docs.python.org/3/faq/design.html#why-are-colons-required-for-the-if-while-def-class-statements
[2] https://docs.python.org/3/faq/design.html#why-does-python-use-indentation-for-grouping-of-statements
? 說明 Description ?
This is a talk on the subject of Python concrete syntax (in a word, the appearance), reading and savoring together the PEG in The Python Language Reference.
I'm going to talk mainly about Compound statements from the reference.
Target statements
Let's read PEG of the following compound statements in this talk:
- if statements
- for statements
- while statements
- Function definitions
- match statements
What's PEG?
Actually, dramatic changes occurred in Python 3.9 silently.
PEP 617 [4] introduces PEG in Python.
Currently the language reference is a mixture of BNF (until Python 3.8) and PEG (from Python 3.9).
I hope this talk helps you read the reference without confusion between BNF and PEG.
[4] https://peps.python.org/pep-0617/
Why this talk?
I have co-authored an introductory Python book for the past few years in Japanese.
Explaining if statements to those who knew nothing about programming and Python was tough for me.
I divided the cases by the presence or absence of else and the number of elifs,
- if ...
- if ... else ...
- if ... elif ... else ...
- e.t.c.
but it was very difficult to verify the omissions in the explanations.
Later, when I read the reference, I was very impressed that the PEG showed the if statement in just two lines without omissions.
Many people may think that the Python Language Reference is difficult, but I hope that more people will become interested in the references by sharing the excitement I gained from them.
I myself have grown as a Python user because of my interest in the language reference, and I think it would be wonderful if this talk leads to the growth of those who listen to it.
I've already talked BNF focused version (30 minutes) in PyCon Kyushu 2022 Kumamoto this January.
Some feedback inspired me to talk about PEG, so wrote this proposal as the updated version.
? 關於講者 About Speaker - nikkie ?
Nikkie began his career as a software engineer in 2016. He started Python as a hobby in 2017 and fell in love with it. He is engaged in Natural Language Processing as a data scientist at Uzabase, inc. Tokyo, Japan from 2019. He is working on the Python community in Japan as a staff of the following event: - [PyCon Japan](https://www.pycon.jp/organizer/index.html): the largest PyCon in Japan - staff on 2019 and 2020 (Program committee, lead on 2020) - [chair](https://pyconjp.blogspot.com/2020/10/pyconjp-2021-chair.html) on 2021 He gave a talk (and lightning talks) at many PyCons in Japan and abroad. - EuroPython 2020, [PyCon APAC 2020](https://youtu.be/JiXnEA7pM7U) (English) He loves anime (Japanese animetation) as much as Python, and implements ideas related to some anime with Python. In 2022, he write code related to "Sing a Bit of Harmony" (e.g. Twitter bot, prototyping AI character, e.t.c.).
#pycontw #pyconapac2022 #python #peg
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https://www.youtube.com/watch?v=0DiDUrhhU30
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/B1nqUTQ1s
?? Slido:https://app.sli.do/event/2odhKfnXyV33Y4yCPDsZdb
? 語言 Language:英文 English
? 層級 Level:中階 Intermediate
? 分類 Category:最佳實踐與慣例 Best Practices & Patterns
? 摘要 Abstract ?
Developers have used Sphinx to integrate documentation into workflow and use tools and services to enhance the developer and user experience from those documentations. This talk will discuss how we further it by utilizing markup processors as extensions and generate more effective documentation. This will be also further elaborated on through a case study showcasing how integrating the documentation can improve the overall benefit towards a project and mistakes to avoid while attempting the integration.
? 說明 Description ?
Documentation is often something developers find tedious and are not exactly enthusiastic about. However, it can be approached very differently; and with this talk, I will able to shed light on the exciting part of documentation with the creation of extensions; in particular over Sphinx. The benefits of Sphinx has been evident to many developers. It has helped in being able to create documentation for our services and put it in such a way that our users and fellow developers enjoy the experience. However, there is so much more to take away from Sphinx than is available from the functionalities that most developers utilize it for, and it all starts with defining our own extensions for it.
This talk will discuss the best practices in creating markup processors as extensions for Sphinx and the benefits it provides users and developers in doing so. This will include how to plan, structure, and catch cases of errors that may come with the extension, as well as specific practices such as with documenting links, references, and in documenting considerations with extensions. This will also include highlighting the current trends in the development of extensions up to this point, and how hierarchy in documentations is being established and structured as a result of this. I will also mention some key points to consider, including making the documentation accessible and managing it as part of the code repository.
At the end of the talk, I will demonstrate this by through a demonstration coupled with talking through a case study of how my own markup processor extension works with Sphinx with its purpose of documenting a custom class type and how I am able to derive benefits from it to better the experience of my users and fellow developers. Users will leave this talk feeling ready to put into practice making new extensions as discussed in this talk as part of their SDLC.
? 講者介紹 About Speaker - Renaldi Gondosubroto ?
Renaldi Gondosubroto is the Founder and CEO of GReS Studio, a company that promotes the concept of the Internet of Things by creating solutions for problems around the community while utilizing the concept. Leading his team of individuals that share the same passion as him with the IoT concept, he leads his company with the vision of being able to have an interconnected world where both individuals and companies can share big data with one another. Starting from just a hobbyist of programming in different languages including Python from a very young age, he eventually decided to venture into working within the IoT technology sector when he created an innovation to help combat a problem all around us which everyone encounters in their daily lives: air pollution. Throughout his time leading his company, Renaldi enjoys sharing his experiences regarding practices and trends that he believes are of importance to develop and navigate through the technologies of today.
#pycontw #pyconapac2022 #python #sphinx #workflow #documentation
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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/BJcR8pmki
?? Slido:https://app.sli.do/event/3ovdbifBx8hXaoWD8EgcxX
? 投影片 Slides:https://bit.ly/pycon22
? 語言 Language:英文 English
? 層級 Level:中階 Intermediate
? 分類 Category:機器學習 Machine Learning
? 摘要 Abstract ?
TensorFlow is an end-to-end open source platform for machine learning. It uses a user-friendly API for defining and training neural networks. It provides stable Python APIs and embraces the style and ergonomics of the Python language. The goal of this talk is to help developers get familiar with this end-to-end platform. To do so, we're going to build an Image Assessment application, TasteGram, completely from scratch all using Python.
? 說明 Description ?
For this talk, we're going to take a top-down approach and start from the aesthetic data. Here, I'll talk about some useful ways of how to preprocess the dataset out of Keras Preprocessing released this year.
And then we'll move on to building and training the model, where we'll get to understand a little bit about how to apply the transfer learning to learn an aesthetic evaluation task.
Finally, we'll tying all of these pieces together at the bottom level and talk a bit about deploying the model on edge devices.
This talk should be pretty helpful for developers to get an idea of how to turn theoretical concepts into working implementations with TensorFlow, and they can develop their own end-to-end ML application all using Python.
? 講者介紹 About Speaker - John Lu ?
John is an Android Developer at Seekrtech, currently focusing on developing a gamified To-do list app, WaterDo. He is deeply motivated by challenges and tends to be excited by breaking conventional ways of thinking and doing. With two years of experience in Machine Learning research, he works on combining the latest AI technology and design to build fun and creative applications.
#pycontw #pyconapac2022 #python #tensorflow #machinelearning #neuralnetwork #tastegram #imageassessment
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Day 1, R0 09:20–10:20
AI is all about training machine to make intelligent decisions automatically—or we may at least dream about that. However, before building a successful AI system, we need to make human choices when developing strategies and setting directions for training machines. For AI system developers, making the right choices is critical to training AI systems into where they are wanted to be, just like a baseball coach who develops strategies and gives instructions to train a winning team. Hsuan-Tien is sharing his thoughts in this keynote on how developers can make good choices for AI before AI can make smarter decisions for you.
Slides: https://drive.google.com/file/d/0B-YWfJ6PLCoJeGRic2NPVDZtNFU/view?usp=sharing
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https://www.youtube.com/watch?v=_kbPKFJY9HQ