JupyterCon
JupyterCon
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Rosio Reyes, Jeremy Tuloup, Eric Charles, Eric Gentry The past, present and future of the Jupyter
Jupyter Notebook 7 is being developed as a replacement for users who may have been previously using Notebook 6 and want more of the features being created for JupyterLab, like real-time collaboration, debuggers, theming, and internationalization, among other benefits. To ensure that those users are equipped with some essential knowledge that will help them smoothly transition to using Notebook 7, this talk will go over some of the key details of working with the new Jupyter Notebook. We will explain how users can run multiple frontends like Notebook 7, JupyterLab and NbClassic (the long term supported version of the Notebook 6 code base) that will ease the transition of users not ready to switch to Notebook 7 as well as give users the freedom to choose between the Notebook 7 and Lab interface based on project needs. Through this talk we will also aim to provide Notebook 6 extension developers with information about the resources available to aid the transition of their extensions to both Notebook 7 and JupyterLab. Notebook users will leave this talk having a better understanding of what next steps they may want to take to get started with Notebook 7.
Переглядів: 606

Відео

Nate Rush De Regid the Widget: Making Jupyter a Haven for Startups | JupyterCon 2023
Переглядів 359Рік тому
Becoming a Widget Author Over the past 2.5 years, I’ve been building a spreadsheet extension for JupyterLab called Mito. This extension needs to share state between the frontend and the backend, and also have the backend/frontend communicate constantly. As such, we naturally built Mito as a Jupyter Widget. Being a widget comes with many benefits, including easy-to-extend templates, automatic sh...
Meag Doherty Maximizing the Impact of User Feedback: Effective Practices for Community Management
Переглядів 115Рік тому
User feedback is crucial to any community, as it helps shape the community’s direction and growth. However, managing and processing this feedback can be challenging, especially for large and active communities. This talk will discuss practices for community management teams to effectively handle user feedback and turn it into valuable insights. We will cover the following topics: Strategies for...
Johan Mabille, Thorsten Beier Xeus kernels in the browser | JupyterCon 2023
Переглядів 351Рік тому
Xeus, a native implementation of the Jupyter protocol, facilitates the authoring of new kernels, especially for languages for which the interpreter has a C or a C API. Kernel authors can focus on the language-specific parts of their work and don’t have to deal with the protocol. The number of flurishing kernels based on xeus these last years has proven it to be a reliable component of the Jupyt...
Fons Van Der Plas Pluto jl - reactive and reproducible notebooks for Julia | JupyterCon 2023
Переглядів 3,3 тис.Рік тому
Slides: gist.github.com/fonsp/b004319fbe728a5fc661ce8ac89c1ac4 Pluto.jl is a new, open source notebook programming environment for Julia, written in Julia and JavaScript. Our mission is to make Julia more accessible and fun! 🎈 In this talk, we would like to introduce Pluto.jl to the JupyterCon audience, and we will talk specifically about our approach to reproducibility and reactivity. While Pl...
Colin Brown Understanding and Visualizing Dependencies between Notebook Cells | JupyterCon 2023
Переглядів 249Рік тому
In Jupyter IPython notebooks, variable declarations are global, so a variable defined in one cell can be referenced, mutated, or redefined in any other cell. Each reference or mutation leads to a cell dependency where one cell should be executed before the other because these dependencies can span the entire notebook and understanding which cells need to be re-executed after a change can be cha...
Carlos Cordoba The Spyder debugger: An interactive debugger based on Jupyter technologies
Переглядів 240Рік тому
One of the main features of scientific programming is its exploratory nature: starting from some input data, the goal is to analyze it in order to understand what it can tell us about the phenomena that generated it. However, the means to do this are often unclear, and the results unforeseen. That is why this type of programming requires tools for rapid, interactive prototyping that allow users...
Amit Rathi, Vinay Kakade Simplify DevOps with Executable Notebooks | JupyterCon 2023
Переглядів 354Рік тому
Today, Jupyter Notebooks are mostly confined to science, research & education. But notebooks can provide organizations with a powerful general-purpose “executable documentation” platform. A solid use case for this is DevOps & more specifically, IT incident response. Technology teams usually have an on-call rotation with static wiki-style documentation to guide the on-call engineer. Jupyter Note...
David Qiu Jupyter AI: Bringing Generative AI to Jupyter | JupyterCon 2023
Переглядів 1,2 тис.Рік тому
Generative artificial intelligence (AI) models are trained to generate new, previously unseen data (text, images, etc.). The generated data is both similar to the training data and a response to a user provided natural language prompt that describes a task or question. Recent generative AI models such as Amazon CodeWhisperer, Codex, Stable Diffusion, and ChatGPT have demonstrated solid results ...
Ana Ruvalcaba, Afshin Darian, Jason Grout, Fernando Pérez State of the Union: Jupyter Community |
Переглядів 246Рік тому
Come learn how the Jupyter community and leadership is organized today. We'll talk about new strategic initiatives impacting the global Jupyter community.
Craig Peters, Cory Gwin GitHub Keynote | JupyterCon 2023
Переглядів 170Рік тому
In the Keynote you will learn about how GitHub expands the reach of the amazing Jupyter technologies
Day 1 Lightning Talks | JupyterCon 2023
Переглядів 204Рік тому
Day 1 Lightning Talks | JupyterCon 2023
Diogo Castro Federated collaborative workflows for Jupyter | JupyterCon 2023
Переглядів 150Рік тому
Cloud Storage for Synchronization and Sharing (CS3) platforms, like ownCloud or Nextcloud, have been widely deployed in the research and educational space, mostly by e-infrastructure providers, NRENs (National Research & Education Networks) and major research institutions. These services, used usually in daily workflows by hundreds of thousands of users (including researchers, students, scienti...
Franklin Koch MyST Markdown: Using notebooks in scientific publishing workflows | JupyterCon 2023
Переглядів 859Рік тому
We introduce mystjs (js.myst-tools.org/), a set of open-source, community-driven tools designed for scientific communication, including a powerful authoring framework that supports blogs, online books, scientific papers, reports and journals articles. The MyST (Markedly Structured Text) project has grown out of the ExecutableBooks team, which has been working on MyST Markdown and JupyterBook as...
Greg Michaelson AutoML as it should have always been | JupyterCon 2023
Переглядів 280Рік тому
When AutoML was popularised during the 2010s, there was a great hope that the citizen data scientist would take over machine learning and that business analysts everywhere would soon be building thousands of advanced AI-based solutions, ushering in the age of AI in business. Not only did that not happen, but even the name “AutoML” has become sullied along with the myth of the citizen data scien...
Jason Grout, Florian Wetschoreck Building on Jupyter at Databricks | JupyterCon 2023
Переглядів 207Рік тому
Jason Grout, Florian Wetschoreck Building on Jupyter at Databricks | JupyterCon 2023
Jeremy Tuloup Creating interactive Jupyter websites with JupyterLite | JupyterCon 2023
Переглядів 690Рік тому
Jeremy Tuloup Creating interactive Jupyter websites with JupyterLite | JupyterCon 2023
Jeremy Tuloup, Johan Mabille Navigating the Jupyter Landscape | JupyterCon 2023
Переглядів 394Рік тому
Jeremy Tuloup, Johan Mabille Navigating the Jupyter Landscape | JupyterCon 2023
Nicolas Poulain Capytale: a case of large scale use of jupyter notebooks in education | JupyterCon
Переглядів 127Рік тому
Nicolas Poulain Capytale: a case of large scale use of jupyter notebooks in education | JupyterCon
Sarah Gibson How to grow the JupyterHub community and improve its practices by mentoring Outreachy
Переглядів 77Рік тому
Sarah Gibson How to grow the JupyterHub community and improve its practices by mentoring Outreachy
Sarah Gibson No Magic Added Deploying Multiple JupyterHubs to Multiple Clouds from one Repositor
Переглядів 132Рік тому
Sarah Gibson No Magic Added Deploying Multiple JupyterHubs to Multiple Clouds from one Repositor
Afshin Darian, Martha Cryan What’s New in JupyterLab 4 0 | JupyterCon 2023
Переглядів 1,1 тис.Рік тому
Afshin Darian, Martha Cryan What’s New in JupyterLab 4 0 | JupyterCon 2023
Alyssa Goodman, A Goodman Alyssa Goodman Keynote | JupyterCon 2023
Переглядів 161Рік тому
Alyssa Goodman, A Goodman Alyssa Goodman Keynote | JupyterCon 2023
Carlos Herrero, Trung Le, David Brochart Real Time Collaboration in Jupyter | JupyterCon 2023
Переглядів 535Рік тому
Carlos Herrero, Trung Le, David Brochart Real Time Collaboration in Jupyter | JupyterCon 2023
Cheuk Ting Ho Driving down the Memray lane Profiling your data science work | JupyterCon 2023
Переглядів 96Рік тому
Cheuk Ting Ho Driving down the Memray lane Profiling your data science work | JupyterCon 2023
Day 2 Lightning Talks | JupyterCon 2023
Переглядів 236Рік тому
Day 2 Lightning Talks | JupyterCon 2023
Fernando Pérez Two decades of IPython and Jupyter
Переглядів 394Рік тому
Fernando Pérez Two decades of IPython and Jupyter
J j Allaire Jupyter Notebooks + Quarto for customizable and reproducible documents, websites and
Переглядів 1,5 тис.Рік тому
J j Allaire Jupyter Notebooks Quarto for customizable and reproducible documents, websites and
Jovan Stojanovic Machine learning with dirty tables: encoding, joining and deduplicating
Переглядів 288Рік тому
Jovan Stojanovic Machine learning with dirty tables: encoding, joining and deduplicating
Luciano Resende, Felipe Barros Elyra an AI development workspace based on Jupyter Notebooks
Переглядів 164Рік тому
Luciano Resende, Felipe Barros Elyra an AI development workspace based on Jupyter Notebooks

КОМЕНТАРІ

  • @oflasch
    @oflasch 7 місяців тому

    Fantastic 😊

  • @chikken007
    @chikken007 7 місяців тому

    Did you progress your open source plans? Would love to use that in practice.

  • @valdemarkatayamakjaer9304
    @valdemarkatayamakjaer9304 9 місяців тому

    Wonderful work! I’m beginning with Julia and one of the main problems of the language, IMO, is the little attention of developers and community towards kids and teens. The language is fantastic for general purpose development (when they create a static compiler it will be unstoppable), but the language needs to get traction from “grassroots “, as Python did do: found in Raspberries Pis, office automation, web scraping etc, home projects, educational projects.

  • @aination7302
    @aination7302 11 місяців тому

    This is not working. Not sure if there is something missing.

  • @olekollo7875
    @olekollo7875 11 місяців тому

    make will Pluto like JupyterLab (UX, etc)

  • @papapatrol
    @papapatrol 11 місяців тому

    Well done lads

  • @pookiepats
    @pookiepats Рік тому

    Awesome

  • @edh615
    @edh615 Рік тому

    protect this man

  • @edh615
    @edh615 Рік тому

    This is extremely nice

  • @jcbritobr
    @jcbritobr Рік тому

    Vary nice stuff

  • @vinayapathak
    @vinayapathak Рік тому

    MyST is fantastic!, Only thing missing is probably, a Markdown like MARP to create presentations directly...Or am I missing anything

  • @张德军-p4j
    @张德军-p4j Рік тому

    But I failed to use it.

  • @Dreaming-11
    @Dreaming-11 Рік тому

    This is a very useful and time-saving feature, I would love to see this in native python...

  • @yosolonopuedo
    @yosolonopuedo Рік тому

    Amazing!

  • @CurioDataPro
    @CurioDataPro Рік тому

    Unfortunately, video is disjointed at 03:20 mark and appears to skip the demo.

  • @andreashon
    @andreashon Рік тому

    incredible package! Have just installed it to try with plots and get just stunned by the intuitive polished interface. Also like for the "no under the hood configs" idea. Everyone should try this!

  • @kostal1991
    @kostal1991 Рік тому

    I really hope that merging Notebook and Lab underlying stacks would make both projects stronger and easier to maintain

  • @Ljupcho
    @Ljupcho Рік тому

    Looks great!

  • @ATT935
    @ATT935 Рік тому

    ok but what about having a real product that can help normal people with real problems? like stress, sleep, focus etc... talking talking but as of right now we have nothing but scammy products on the market that do nothing of value

  • @jackyarcher9749
    @jackyarcher9749 Рік тому

    'promo sm' 🙈

  • @jhonyortiz5
    @jhonyortiz5 Рік тому

    Ummmmmm I don't know about this.

  • @andrewm4894
    @andrewm4894 Рік тому

    As someone who studied economics and works in ml and open source this is such a niche little treat for me lol :) Cool to see someone like Paul Romer so engaged here, great stuff!

  • @fmcea
    @fmcea Рік тому

    stylé

  • @vishnukv5988
    @vishnukv5988 2 роки тому

    HI, thanks for the video. I have a doubt. If I want to do some preprocessing in the jupyter notebook and then run the fastapi how do I do that? Like I have to run cells 1,2,3,4 before calling the model. Thanks in advance

  • @viveklakhataria8281
    @viveklakhataria8281 2 роки тому

    HI how to publish custom extension

    • @asanchez4949
      @asanchez4949 4 місяці тому

      My dude this is a youtube comment not google search

  • @viniciussebbapatto7859
    @viniciussebbapatto7859 2 роки тому

    It's so beautiful but, in Brazil, FB has done the exact opposite, it is reducing the spread of truth and trying to turn lies into truths. t's a shame this attempt to censor people arround the world.

  • @sachinkaushik7844
    @sachinkaushik7844 2 роки тому

    HI Team, We have a requirement where we want to show session time on JupyterLab’s top bar, whenever User get access to JupyterLab. Let say we have session time 2Hrs, then in this case it should be shown on Jupyterlab. Do we have any such configuration file where we can make changes related to session time configuration. Please help me here. Thank you in advance.! Thanks, Sachin

  • @سموالاسمري
    @سموالاسمري 3 роки тому

    نايس

  • @clarcktumazar
    @clarcktumazar 3 роки тому

    Hi! is Bento exclusive only for Facebook or is it available publicly?

  • @MichaelTiemann
    @MichaelTiemann 3 роки тому

    This is an incredible demo. Hats off, Simon!!

  • @gregmerritt6630
    @gregmerritt6630 3 роки тому

    Rick, thank you for this: super clear, super informative, and very nicely presented!

  • @ryanlovett9953
    @ryanlovett9953 4 роки тому

    Re: 10:19, I searched for "nbdashboard", but it is actually "nvdashboard", i.e. jupyterlab-nvdashboard.

  • @nguyenngocly1484
    @nguyenngocly1484 4 роки тому

    You need the Walsh Hadamard transform to experiment with inside-out neural networks. With fixed dot-products (weighted sums) and adjustable (parametric) activation functions. The fast transform providing the fixed dot products.

  • @kianafarhadyar902
    @kianafarhadyar902 4 роки тому

    Thank you for the very nice talk :)