PyData NYC转发了
The call for proposals for PyData Paris 2025 is now open! Don't delay, get your submissions early. CfP Deadline: Sunday 13th April 2025 ?? Cité des sciences et de l'industrie ?? September 30th and October 1st. pydata.org/paris2025/cfp
PyData NYC
软件开发
New York，New York 1,709 位关注者
The New York City area chapter of PyData, a community of developers and users of open source data tools.
关于我们
PyData NYC can only become a successful event with your involvement! We are a community-driven event, and we love seeing new faces. Whether you’re interested in giving a talk or sponsoring our event, we’d love to hear from you! For Speakers: If you have an exciting project, research, or technology to share, we welcome you to speak at our meetup events. For Sponsors: Supporting our meetups can help foster the growth of the data science community, gain exposure, and connect with industry experts Fill out our interest form to get started: https://docs.google.com/forms/d/e/1FAIpQLSdPgj22St-VAw-el_LGImbWUrlff3EXfm6ghlCrYcb9_2G4-w/viewform Check meetup.com/pydatanyc for all upcoming events
- 网站
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https://meetup.com/pydatanyc
PyData NYC的外部链接
- 所属行业
- 软件开发
- 规模
- 2-10 人
- 总部
- New York，New York
- 类型
- 非营利机构
- 创立
- 2012
- 领域
- Python、Data science、Data visualization、Julia、R和Open source
地点
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主要
获取路线
US，New York，New York，10036
动态
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PyData NYC转发了
????Pushing Cython to its limits in scikit-learn Check out the PyData NYC 2024 presentation by maintainer Thomas J. Fan scikit-learn is a machine-learning library for Python that uses NumPy and SciPy for numerical operations. Scikit-learn has its own compiled code for performance-critical computation written in C, C++, and Cython. The library primarily focuses on Cython for compiled code because it is easy to use and approachable. In this talk, we dive into many techniques scikit-learn employs to utilize Cython fully. We will cover features like using the C++ standard library within Cython, fused types, code generation with the Tempita engine, and OpenMP for parallelization. #opensource #python #machinelearning #datascience https://lnkd.in/e27AhKUz
Thomas J. Fan - Pushing Cython to its Limits in Scikit-learn | PyData NYC 2024
https://www.youtube.com/
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PyData NYC转发了
Following on the footsteps of our massively successful PyData Boston event in January, happy to announce our February event with some fantastic speakers: https://lnkd.in/gwRQ76Dv RSVP's close 2/24, so RSVP soon!
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PyData NYC转发了
?? 13 days left ! Register as a speaker for PyData London 2025 ?? https://lnkd.in/e-YX9JRh
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PyData NYC meetups host a great variety of people from different types of organizations both public and private. They come from large tech companies such as Microsoft , Google , IBM, Meta, and NVIDIA to small startups, along with members of other industries such as finance, healthcare, and beyond. All of these different players use many of the same underlying libraries, tools, and frameworks that are maintained by our parent organization NumFOCUS including NumPy, Pandas, Polars, and over 70 other projects. https://lnkd.in/gF35jPxz #Python #Datascience #AI
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Join PyData NYC at 11 Times Square (Microsoft) on Feb 12th at 6:30 pm for a talk night with Tamer Abuelsaad (Emergence AI). ?? Pizza, drinks & venue sponsored by Emergence AI- thank you! Navigating the Web: Lessons from Building Real-World Agents How do you create agents that reliably move through websites and perform complex tasks? In this talk, we’ll share Emergence AI’s journey of building and refining web navigation agents using different techniques. This talk will cover what worked well, what didn’t, and the practical lessons learned along the way. Register here: https://lnkd.in/gGn54tKA #Python #DataScience #AI #Agents
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PyData NYC转发了
My lightning talk recording from PyData NYC is up! I'm talking about EffVer, the version scheme where you just tell your users what order of mangnitude to expect the upgrade effort to be. YouTube Recording: https://lnkd.in/ejPs8Q98 Blog post: https://lnkd.in/ep742MFz
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Thank you for the talk! Many more from the most recent conference can be found here: https://lnkd.in/gttX5jQv
This video is a GOLDMINE of information about Python in Excel. Much of it you won't find anywhere else. I'm certain of that. ?????? One of the great privileges I have working at Anaconda, Inc. is that I get to talk with Jim Kitchen about Python in Excel. If you happened to be at PyData NYC this past November, you had the opportunity to dive deep on that topic and on a few things which I think are particularly fascinating: - Customizing the xl() method - shown in the image is a custom xl() method that allows us to specify the return type when we use it - Custom object reprs (i.e. custom card views and custom Excel values) - Anaconda Code, including Python User-Defined Funcions! I'm certain that people interested in Python in Excel will benefit a great deal by watching it all, but I know that finding 90 minutes to spare these days is probably not easy, so this morning I've added timestamps to the video in a comment so that you can, if you want, see it as a kind of playlist to be watched over a period of days. https://lnkd.in/gE34epcC I hope you find it interesting. I know I did. #data #analytics #python #excel #pythoninexcel #anaconda
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Thank you to NVIDIA for their support of this year's conference!
? We are excited to share our on-demand resources from #PyDataNYC to help you accelerate Python with GPU acceleration. In this tutorial, we’ll explore the CUDA-enabled Python ecosystem, working through hands-on examples with top accelerated scientific computing libraries. ??? ?? All resources are on Colab—follow along with our NVIDIA experts step by step bit.ly/3P96GuQ
McCarty, Riehl, & Tomlinson - GPU Accelerated Python | PyData NYC 2024
https://www.youtube.com/
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PyData NYC转发了
“It is through funding that we’re able to grow our community”, says Ryan Curtin from mlpack. Listen to him discuss the importance of funding and supporting our projects, and donate to our End-of-Year Fundraiser today to make an impact on the future of open source yourself! ???? Stable funding, from sources like the NumFOCUS Small Developer Grants, is essential for creating and maintaining high-quality open source projects. Funding enables contributors to focus on development and tackle difficult yet necessary tasks like documentation and technical debt management. NumFOCUS Small Development Grants foster a strong community by supporting new contributors and students, helping them feel connected, invested, and stable in the project. Hear it directly from 15-year mlpack maintainer Ryan Curtin, and make your donation today by investing in #OpenCode4BetterScience! https://hubs.la/Q030ffBk0 All funds, except those directed to a specific project, will go toward our Small Development Grants.