In this talk, we’ll learn about a highly controversial proposed change to Python syntax, the rationale for it, and the fallout as the result of it.
Slides not uploaded by the speaker.
Speaker: Dustin Ingram
Dustin is a Developer Advocate at Google, focused on supporting the Python community on Google Cloud. He's also a member of the Python Packaging Authority, maintainer of PyPI, organizer for the PyTexas conference. ... https://www.youtube.com/watch?v=F5cPSzEcVQs
PyCon Taiwan 2023|Talk 演講|Day 2, R2 13:05–13:35
? 說明 Description ?
The intersection of UX and Python programming is a powerful combination for building great products and enhancing user experience. Python is a versatile and popular programming language that is widely used for a variety of tasks, including web development, data analysis, and machine learning. UX, or user experience, is the process of designing products that provide a seamless and intuitive experience for users.
Learn about this powerful intersection of UX design and Python programming by understanding how Python can be used to enhance the user experience and provide practical examples on how UX designers can automate tasks, gather and analyze data, develop personalized experiences, and continually improve their own skills and processes.
? 講者介紹 About Speaker - Neeraj Pandey ?
Neeraj is a polyglot and open-source contributor. Over the years, he has spoken at multiple international Python conferences and has worked on a variety of full-stack software and data science applications, as well as computational arts and quantitative finance projects. He enjoys the challenge of creating new tools and applications.
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https://www.youtube.com/watch?v=zOS5ciDrdqg
Day 1, 16:15 ~ 17:15
AI assistants are the new faces of tech. We can now control our lights, play music, make an account transfer, and buy insurance from a chat or voice interface. Conversational AI opens up tech further to serve the people who were once left behind.
Building AI assistants from scratch is very challenging. But now, we have much better tooling and infrastructure that make use of cutting-edge NLP research. In this talk, we will explore the current state of the technology: the level of experience we can provide for the end-user, the ease of building AI assistants from the dev perspective, and the maturity across different languages. We’ll also pull up our sleeves and develop an AI assistant together!
Slides not uploaded by the speaker.
HackMD: https://hackmd.io/@pycontw/2021/%2F%40pycontw%2FH1HD2WYGY
Speaker: Yenny Cheung
Originally from Hong Kong, Yenny is an engineering leader at Rasa. She and her team are working on the standard open-source infrastructure for building Conversational AI. She writes and speaks about Conversational AI, engineering management, and Python best practices. She cares about building inclusive teams with a “people first” approach. She enjoys the thrill of public speaking and meeting like-minded people along the way. You can find her on Twitter and at conferences on leadership and Python. She is also an angel investor backing founders from underrepresented backgrounds.
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https://www.youtube.com/watch?v=mZDmGP0OWv4
Speaker: Wisely Chen
Apache Spark™ is a lightning fast engine for large-scale data processing. It is an in-memory cluster computing framework, originally developed in UC Berkeley. Base on it's project page's evaluation, machine learning programming can run program 100x faster than Hadoop MapReduce. And Spark can run on Hadoop 2's YARN cluster manager, and can read any existing Hadoop data. Currently, it supports Scala, Java and Python for writing spark programs.
In this talk, I will introduce the General concept of Spark's infrastructure, What is RDD (Resilient Distributed Datasets) in Spark, Introduction on PySpark, Demo of PySpark's speed and power, Head-to-head comparison between two programs doing same work - one written in Hadoop MapReduce and the other written using PySpark.
I will also conclude about the companies currently using Spark's use cases.
About the speaker
Sr. Software Engineer for the Yahoo! (Taiwan) Data Team. He has been responsible for data infrastructure, data solution, software release and continuous integration management. He is a lifelong student of software development/testing/deployment/CI processes and best practices and an avid coding puzzle competition fanatic as well as Open Source evangelist
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https://www.youtube.com/watch?v=gaR7svYX8pw
The Internet of Things Concept has become a trending, booming concept in today's time, and almost every tech enthusiast would know it. It is being used all over the place; starting from in homes to being used in big scale appliances such as building the smart city. In this talk, I will be going over how the concept has been applied in Python over time and how it has progressed thus far. I will relate to some projects that implement the IoT concept within Python (including some of my own for reference) to further illustrate how it has become widely applied in many cases, from some simple ones to some also from an advanced level. I will then further talk about how this has been very beneficial from a consumer standpoint, and how the methodology of its usage can be developed with practical uses. After that, I will talk about the future of this concept within Python, and how I see this concept will grow in this platform, and the future developments that can still be done through here.
PyCon Taiwan 2017 official: https://tw.pycon.org/2017/
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https://www.youtube.com/watch?v=ELkdp0Akbr8