Podcasts about jupytercon

We all know that LLMs and generative AI has been working its way into many products. It's Jupyter's turn to get a really awesome integration. We have David Qiu here to tell us about Jupyter AI. Jupyter AI provides a user-friendly and powerful way to apply generative AI to your notebooks. It lets you choose from many different LLM providers and models to get just the help you're looking for. And it does way more than just a chat pane in the UI. Listen to find out. Links from the show David Qiu: linkedin.com Jupyter AI: jupyter-ai.readthedocs.io Asking about something in your notebook: jupyter-ai.readthedocs.io Generating a new notebook: jupyter-ai.readthedocs.io Learning about local data: jupyter-ai.readthedocs.io Formatting the output: jupyter-ai.readthedocs.io Interpolating in prompts: jupyter-ai.readthedocs.io JupyterCon 2023 Talk: youtube.com PyData Seattle 2023 Talk: youtube.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy Sponsors Posit Talk Python Training

Jupyter Notebooks and Jupyter Lab have to be one of the most important parts of Python when it comes to bring new users to the Python ecosystem and certainly for the day to day work of data scientists and general scientists who have made some of the biggest discoveries of recent times. And that platform has recently gotten a major upgrade with JupyterLab 4 released and Jupyter Notebook being significantly reworked to be based on the changes from JupyterLab as well. We have an excellent panel of guests, Sylvain Corlay, Frederic Collonval, Jeremy Tuloup, and Afshin Darian here to tell us what's new in these and other parts of the Jupyter ecosystem. Links from the show Guests Sylvain Corlay Frederic Collonval Jeremy Tuloup Afshin Darian JupyterLab 4.0 is Here: blog.jupyter.org Announcing Jupyter Notebook 7: blog.jupyter.org JupyterCon 2023 Videos: youtube.com Jupyterlite: github.com Download JupyterLab Desktop: github.com Mythical Man Month Book: wikipedia.org Blender in Jupyter: twitter.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy Sponsors Phylum Python Tutor Talk Python Training

Topics covered in this episode: Django 5.0 beta 1 released git bash, terminals, and Windows Mastering Integration Testing with FastAPI Reuven Learner has been banned for trading in rare animals (Pythons and Pandas) Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org Brian: @brianokken@fosstodon.org Show: @pythonbytes@fosstodon.org Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesdays at 11am PT. Older video versions available there too. Brian #1: Django 5.0 beta 1 released Django 5.0 release notes supports Python 3.10, 3.11, 3.12 Facet filters in the admin Simplified templates for form field rendering Database-computed default values Database generated model field More options for declaring field choices More Django news Djangonaut Space now accepting applications for our next contributor mentorship cohort Take the Django Developers Survey 2023 Michael #2: git bash, terminals, and Windows See the screenshot Requires Windows 10 Install the Windows Terminal from the Microsoft Store Brian #3: Mastering Integration Testing with FastAPI Alex Jacobs Some great integration testing techniques Focused on FastAPI, but relevant to many frameworks. Mocking authentication Mocking external APIs Fun use of parametrize and indirect fixtures for mocking responses. Mocking MongoDB Mocking AWS S3 Michael #4: Reuven Learner has been banned for trading in rare animals (Pythons and Pandas) via Pat Decker Reuven, like us, teaches Python and Data Sci Tried to advertise his courses (Python and Pandas courses) on Meta Got permanently (life-time) banned for selling rare and endangered animals. Sometimes I really hate these big tech companies My recent beefs have been with app store reviewers and surveillance-based capitalism Extras Brian: Where did everyone go? - Ned Batchelder I do feel like we're more fragmented than before, but I am feeling like we have a community on Mastodon. reminder that Mastodon has text search now On Sunday, I released Ch9, Coverage, as part of The Complete pytest course, specifically part of pytest Working with Projects. It was super fun. I've used coverage a lot since writing the book, for example, I demonstrate branch coverage. It's so much more effective to teach in video than in printed screenshots. Michael: Autin shell enhancer by Ellie Huxtable recommended by recommended by Nik JupyterCon 2023 videos are out More shells follow up from Teemu Hukkanen for “editor like” features Zsh and Bash ruff format and strings, aka format.quote-style = "single" Glyph's programming your computer talk is up. Joke: this is what the experts do

Panelists Eriol Fox | Katie Wilson | Meag Doherty Show Notes Welcome to Sustain Open Source Design! In this second part of a series of podcasts about the user work, Eriol is joined by Katie Wilson and Meag Doherty to discuss their project, Superbloom, which delves into design and usability in scientific and research open source software. Today, they shed light into the ideal user type of open source software tools, the focus on software maintainability in design, and how software complexity plays into its perceived value in decision-making, and how it may impact the progress of open science. They also discuss the necessity of usability in decision-making, and how it may impact the progress of open science, and they highlight their experiences at various events and initiatives that underscore the importance of continuing conversations around these topics. Hit download now to hear more! [00:01:14] Katie Wilson, a Design Researcher at Superbloom and Meag Doherty, the Deputy Chief User Experience Officer at the All of Us Research Program, introduce themselves and we'll hear what their relationship is to the project. [00:04:17] Eriol introduces the topic of end users and discusses the discovery that most open source software tools, including those in scientific and research domains, seem to have an ideal user type with particular skills and capabilities. [00:07:05] Katie continues the conversation, mentioning that when asked about design, many open source software projects focus on making the software as maintainable and contributable as possible, thus often perceiving the users as fellow programmers or contributors. [00:09:25] Eriol shares one last thought on the usability chapter and comments on how complexity in scientific and research open source software could be viewed as a safety aspect that validates their relevance in the field. [00:11:30] Meag segues to the potential impact of these findings. She emphasizes that usability is not an afterthought but central to the decision-making process, and poor usability could hinder the progress of open science. [00:12:59] Katie addresses UX best practices in the context of scientific software, suggesting that the tool's complexity might dictate its user experience. [00:14:52] Eriol talks about accessibility. They explain that designers view accessibility from a different perspective that scientists or researchers in the open source software space. However, for non-designers, accessibility is understood, as broadening the tool's application and potential discovery of science and research. [00:19:21] The conversation shifts to Meag talking about incentives, particularly within university settings and academic groups. She stresses the importance of understanding incentives and looking for windows of opportunity to implement usability improvements. [00:20:13] Eriol describes some work done by their colleagues, who created a series of informative zines distilling complex research findings into six-page summaries. [00:22:50] Katie discusses an ecosystem map they developed to visualize interconnected projects, institutions, and contributors within the scientific and research open-source software space. [00:24:15] Meag talks about a trip to an open source science retreat in Germany where the focus was on the usability of software used by research software engineers daily. She also mentions more of their work was shared at the Software Sustainability Institute's Collaboration Workshop and at JupyterCon 2023 in Paris. [00:27:24] Eriol affirms the importance of welcoming new people into the space to sustain and improve usability design, highlighting the need to include people from the peripheries of science, research, and open source. Spotlight [00:29:21] Eriol's spotlight is a project funded by the Vermont Complex Systems that was a series of weekly designer diary studies that designers did over 10 weeks that they coordinated at Superbloom. [00:30:25] Meag's spotlight is The White House Office of Science and Technology Policy that has taken big steps to do listening sessions. [00:31:08] Katie's spotlight is the project, AutSPACEs, a platform where autistic people can report their experiences on sensory processing differences in everyday life. Links Open Source Design Twitter (https://twitter.com/opensrcdesign) Open Source Design (https://opensourcedesign.net/) Sustain Design & UX working group (https://discourse.sustainoss.org/t/design-ux-working-group/348) SustainOSS Discourse (https://discourse.sustainoss.org/) Sustain Open Source Twitter (https://twitter.com/sustainoss?lang=en) Richard Littauer Twitter (https://twitter.com/richlitt?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor) Eriol Fox Twitter (https://twitter.com/EriolDoesDesign?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor) Katie Wilson LinkedIn (https://www.linkedin.com/in/katie-wilson-283491114) Meag Doherty Twitter (https://twitter.com/EmDohh) Superbloom (https://simplysecure.org/blog/introducing-superbloom/) Superbloom Twitter (https://twitter.com/sprblm_) All Of Us Research Program (https://www.joinallofus.org/) “Research software engineering accelerates the translation of biomedical research for health”-Nature Medicine article (June 1, 2023) (https://www.nature.com/articles/s41591-023-02353-0) Diary-Studies-Designers-in-OSS (https://github.com/simplysecure/Diary-Studies-Designers-in-OSS) JupyterCon 2023 (https://www.jupytercon.com/) Software Sustainability Institute Collaborations Workshop 2023 (https://www.software.ac.uk/cw23) Vermont Complex Systems Center (https://vermontcomplexsystems.org/) The White House-Office of Science and Technology Policy-Events & Webinars (https://www.whitehouse.gov/ostp/events-webinars/) AutSPACEs (https://github.com/alan-turing-institute/AutSPACEs) Credits Produced by Richard Littauer (https://www.burntfen.com/) Edited by Paul M. Bahr at Peachtree Sound (https://www.peachtreesound.com/) Show notes by DeAnn Bahr Peachtree Sound (https://www.peachtreesound.com/)

JupyterCon 2023, the conference on all things Jupyter was held in Paris between 10-12 May 2023, followed by 2 days of hands-on "sprints". Jupyter is a very popular open source platform with tools such as Jupyter notebook/lab and driven by a very active community. There were a number of excellent talks from a range of different subjects. I had the pleasure to meet and talk to a number of people, see the interview list below.Order of Interviews: Leah Silen and Arliss Collins from Numfocus  02:04Franklin Koch (MyST) from Curvenote 04:59Nicolas Thiery (Paris-Saclay) 09:13Sarah Gibson (2i2c) 13:19Ana Ruvalcaba (Jupyter Executive Council) 18:57Fernando Perez (Jupyter Executive Council) 23:48Raniere de Silva (Gesis) 29:56Linkshttps://jupyter.org Jupyter projecthttps://jupyter.org/enhancement-proposals/79-notebook-v7/notebook-v7.html# Release notes for the new Jupyter Notebook v7https://jupyterlab.readthedocs.io/en/latest/getting_started/changelog.html#v4-0 Release notes for JupyterLab v4.0 (further incremental updates of v4 are available)https://www.youtube.com/@JupyterCon YouTube channel for JupyterCon 2023https://cfp.jupytercon.com/2023/schedule/ JupyterCon 2023 schedulehttps://www.outreachy.org Outreachy project https://numfocus.org Numfocus projecthttps://data.agu.org/notebooks-now/ Notebooks Now initiativehttps://myst-tools.org MyST tool for scientific and technical communicationUpcoming RSE conferences:https://rsecon23.society-rse.org UK RSE conference in Swansea 5-8 Sep 2023https://hidden-ref.org/festival-of-hidden-ref/ Hidden Ref in Bristol, UK, 21 Sep 2023https://un-derse23.sciencesconf.org Unconference of the German RSE society deRSE in Jena 26-28 Sephttps://us-rse.org/usrse23/ 1st face to face US RSE Conference in Chicago 16-18 Oct 2023Support the Show.Thank you for listening and your ongoing support. It means the world to us! Support the show on Patreon https://www.patreon.com/codeforthought Get in touch: Email mailto:code4thought@proton.me UK RSE Slack (ukrse.slack.com): @code4thought or @piddie US RSE Slack (usrse.slack.com): @Peter Schmidt Mastadon: https://fosstodon.org/@code4thought or @code4thought@fosstodon.org LinkedIn: https://www.linkedin.com/in/pweschmidt/ (personal Profile)LinkedIn: https://www.linkedin.com/company/codeforthought/ (Code for Thought Profile) This podcast is licensed under the Creative Commons Licence: https://creativecommons.org/licenses/by-sa/4.0/

Les références : Jupyter, (fiche wikipédia) Émission « Libre à vous ! » du 1er février 2022 sur la science ouverte Capytale, un environnement de travail standardisé conçu pour l'enseignement scolaire À la découverte de l'écosystème Jupyter et des carnets numériques le site de JupyterConQuantStackVous pouvez commenter les émissions, nous faire des retours pour nous améliorer, ou encore des suggestions. Et même mettre une note sur 5 étoiles si vous le souhaitez. Il est important pour nous d'avoir vos retours car, contrairement par exemple à une conférence, nous n'avons pas un public en face de nous qui peut réagir. Pour cela, rendez-vous sur la page dédiée.Pour connaître les nouvelles concernant l'émission (annonce des podcasts, des émissions à venir, ainsi que des bonus et des annonces en avant-première) inscrivez-vous à la lettre d'actus.

MLOps Coffee Sessions #62 with Joel Grus, MLOps from Scratch. // Abstract In this talk, Joel Grus of “I don't like notebooks” fame shares with us his 2021 perspective on notebooks, where he thinks MLOps is now, and what his hot takes in the data space are now. // Bio Joel Grus is a Principal Engineer at Capital Group, where he leads a team that builds search, data, and machine learning products for the investment group. He is the author of the bestselling O'Reilly book *Data Science from Scratch*, the not-bestselling self-published book *Ten Essays on Fizz Buzz*, and the controversial JupyterCon talk "I Don't Like Notebooks." He recently moved to Texas after living in Seattle for a very long time. // Relevant Links Data Science from Scratch book: https://www.oreilly.com/library/view/data-science-from/9781491901410/ Data Science from Scratch, 2nd Edition book: https://www.oreilly.com/library/view/data-science-from/9781492041122/ Ten Essays on Fizz Buzz: Meditations on Python, mathematics, science, engineering, and design book: https://www.amazon.com/Ten-Essays-Fizz-Buzz-Meditations/dp/0982481829 or https://leanpub.com/fizzbuzz/ I Don't Like Notebooks talk: https://www.youtube.com/watch?v=7jiPeIFXb6U I Don't Like Notebooks - #JupyterCon 2018 slides: https://docs.google.com/presentation/d/1n2RlMdmv1p25Xy5thJUhkKGvjtV-dkAIsUXP-AL4ffI/edit#slide=id.g362da58057_0_658 Fizz Buzz in Tensorflow: https://joelgrus.com/2016/05/23/fizz-buzz-in-tensorflow/ --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Catch all episodes, Feature Store, Machine Learning Monitoring and Blogs: https://mlops.community/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Vishnu on LinkedIn: https://www.linkedin.com/in/vrachakonda/ Connect with Joel on LinkedIn: https://www.linkedin.com/in/joelgrus/ Timestamps: [00:00] Introduction to Joel Grus [01:32] Joel's background in tech [07:47] Joel's I Don't Like Notebooks talk on Jupyter Con [13:42] Better tooling around notebooks [16:48] Hex [17:20] Step function evolution [20:41] Kinds of professionals required in Joel's organization to practice MLOps [23:08] Evaluation process [25:51] Sagemaker bring your own algorithm [27:30] Flexibility of models [31:55] Hot takes on data science world [34:19] Current Overall Maturity of MLOps [37:23] Kinds of problem in NLP and search [39:52] Finding ways to put structures [40:50] Probabilistic nature of machine learning systems [43:10] Data scientists coping up on writing production code [46:33] Invaluability of code review [47:22] Common repo structure [47:57] Reviewing codes [49:15] Code pals [50:36] Readability and function [52:23] Leverage code review [53:10] Remote work

PyChat: PyData global CfP is opened JupyterCon 2020 Virtual Event PyTorch joins NumFOCUS as an Affiliated Project PyGotham TV - last days for CfP (July 5th) Python Ireland remote meetup events > volunteers for Lightning Talks Blog about Pickle: Pickle's nine flaws Mid Meet - Hall of Fame Interview with Waylon Walker (Twitter & dev.to)- Data driven solution enabler, creator of find-kedro and kedro-static-viz

This week, Jon Foust and Michelle Casbon bring you another fascinating interview from our time at Next! Michelle and special guest Amanda were able to catch up with Paco Nathan of Derwen AI to talk about his experience at Next and learn what Derwen is doing to advance AI. Paco and Derwen have been working extensively on ways developer relations can be enhanced by machine learning. Along with O’Reilly Media, Derwen just completed three surveys, called ABC (AI, Big Data, and Cloud), to look at the adoption of AI and the cloud around the world. The particular interest in these studies is a comparison between countries who have been using AI, Big Data, and Cloud for years and countries who are just beginning to get involved. One of the most interesting things they learned is how much budget companies are allocating to machine learning projects. They also noticed that more and more large enterprises are moving, at least partially, to the cloud. One of the challenges Paco noticed was the difference between machine learning projects in testing versus how they act once they go live. Here, developers come across bias, ethical, and safety issues. Good data governance polices can help minimize these problems. Developing good data governance policies is complex, especially with security issues, but it’s an important conversation to have. In the process of computing the survey data, Paco discovered many big companies spend a lot of time with this issue and even employ checklists of requirements before projects can be made live. In his research, Paco also discovered that about 54% of companies are non-starters. Usually, their problems stem from tech debt and issues with company personnel who do not recognize the need for machine learning. The companies working toward integrating machine learning tend to have issues finding good staff. Berkeley is working to solve this problem by requiring data science classes of all students. But as Paco says, data science is a team sport that works well with a team of people from different disciplines. Paco is an advocate of mentoring, to help the next generation of data scientists learn and grow, and of unbundling corporate decision making to help advance AI. Amanda, Michelle, and Paco wrap up their discussion with a look toward how to change ML biases. People tend to blame ML for bias outcomes, but models are subject to data we feed in. Humans have to make decisions to work around that by looking at things from a different perspective and taking steps to avoid as much bias as we can. ML and humans can work together to find these biases and help remove them. Paco Nathan Paco Nathan is the Managing Parter at Derwen. He has 35+ years tech industry experience, ranging from Bell Labs to early-stage start-ups. Paco is also the Co-chair Rev. Advisor for Amplify Partners, Recognai, Primer AI, and Data Spartan. He was formerly the Director of Community Evangelism for Databricks and Apache Spark. Cool things of the week CERN recreated the Higgs discovery on GCP video To discover the Higgs yourself, check out the CERN open data portal site Fun facts from Michelle’s visit: Seven total, four main experiments ATLAS (largest, general-purpose) site CMS (prettiest, general-purpose) site ALICE (heavy-ion) site LHCb (interactions of b-hadrons, matter/antimatter asymmetry) site The French/Swiss border runs across the CERN property Streetview of CERN control center site CERN is the birthplace of the web Where the protons come from site Watch Particle Fever movie Interview Derwen, Inc. site Derwen, Inc. Blog blog Cloud Programming Simplified: A Berkeley View on Serverless Computing paper Apache Spark site Google Cloud Storage site Datastore site Kubeflow site Quicksilver site O’Reilly Media site Google Knowledge Graph site Jupyter site JupyterCon site The Economics of Artificial Intelligence site “Why Do Businesses Fail At Machine Learning?” by Cassie Kozyrkov video The Gutenberg Galaxy site Programmed Inequality site Question of the week Stadia Connect occurred last Thursday. What are some of the biggest announcements that came out of it? Where can you find us next? Jon is in New York for Games for Change. Michelle and Mark Mirchandani are back in San Francisco. Brian & Aja are at home in Seattle. Gabi is in Brazil. Sound Effect Attribution “Crowd laugh.wav” by tom_woysky of Freesound.org

Jessica Forde, Yuvi Panda and Chris Holdgraf join Melanie and Mark to discuss Project Jupyter from it’s interactive notebook origin story to the various open source modular projects it’s grown into supporting data research and applications. We dive specifically into JupyterHub using Kubernetes to enable a multi-user server. We also talk about Binder, an interactive development environment that makes work easily reproducible. Jessica Forde Jessica Forde is a Project Jupyter Maintainer with a background in reinforcement learning and Bayesian statistics. At Project Jupyter, she works primarily on JupyterHub, Binder, and JuptyerLab to improve access to scientific computing and scientific research. Her previous open source projects include datamicroscopes, a DARPA-funded Bayesian nonparametrics library in Python, and density, a wireless device data tool at Columbia University. Jessica has also worked as a machine learning researcher and data scientist in a variety of applications including healthcare, energy, and human capital. Yuvi Panda Yuvi Panda is the Project Jupyter Technical Operations Architect in the UC Berkeley Data Sciences Division. He works on making it easy for people who don’t traditionally consider themselves “programmers” to do things with code. He builds tools (e.g., Quarry, PAWS, etc.) to sidestep the list of historical accidents that constitute the “command line tax” that people have to pay before doing productive things with computing. Chris Holdgraf Chris Holdgraf is a is a Project Jupyter Maintainer and Data Science Fellow at the Berkeley Institute for Data Science and a Community Architect at the Data Science Education Program at UC Berkeley. His background is in cognitive and computational neuroscience, where he used predictive models to understand the auditory system in the human brain. He’s interested in the boundary between technology, open-source software, and scientific workflows, as well as creating new pathways for this kind of work in science and the academy. He’s a core member of Project Jupyter, specifically working with JupyterHub and Binder, two open-source projects that make it easier for researchers and educators to do their work in the cloud. He works on these core tools, along with research and educational projects that use these tools at Berkeley and in the broader open science community. Cool things of the week Dragonball hosted on GC / powered by Spanner blog and GDC presentation at Developer Day Cloud Text-to-Speech API powered by DeepMind WaveNet blog and docs Now you can deploy to Kubernetes Engine from Gitlab blog Interview Jupyter site JupyterHub github Binder site and docs JupyterLab site Kubernetes site github Jupyter Notebook github LIGO (Laser Interferometer Gravitational-Wave Observatory) site and binder Paul Romer, World Bank Chief Economist blog and jupyter notebook The Scientific Paper is Obsolete article Large Scale Teaching Infrastructure with Kubernetes - Yuvi Panda, Berkeley University video Data 8: The Foundations of Data Science site Zero to JupyterHub site JupyterHub Deploy Docker github Jupyter Gitter channels Jupyter Pop-Up, May 15th site JupyterCon, Aug 21-24 site Question of the week How did Google’s predictions do during March Madness? How to build a realt time prediction model: Architecting live NCAA predictions Final Four halftime - fed data from first half to create prediction on second half and created a 30 second spot that ran on CBS before game play sample prediction ad Kaggle Competition site Where can you find us next? Melanie is speaking about AI at Techtonica today, and April 14th will be participating in a panel on Diversity and Inclusion at the Harker Research Symposium

In this episode of the Data Show, I spoke with Jesse Anderson, managing director of the Big Data Institute, and my colleague Paco Nathan, who recently became co-chair of Jupytercon. This conversation grew out of a recent email thread the three of us had on machine learning engineers, a new job role that LinkedIn recently pegged […]

Hilary and Roger have a late-night discussion about JupyterCon, data analysis and decisions, and other deeper topics. Show Notes: JupyterCon: https://conferences.oreilly.com/jupyter/jup-ny Financial stability monitor: https://www.financialresearch.gov/financial-stability-monitor/ Catistician: https://twitter.com/ChelseaParlett/status/902581025175429120 Tyranny of Structurelessness: http://www.jofreeman.com/joreen/tyranny.htm Data Alone Isn’t Ground Truth (by Angela Bassa): https://medium.com/@angebassa/data-alone-isnt-ground-truth-9e733079dfd4 Support us through our Patreon page: https://www.patreon.com/NSSDeviations Roger on Twitter: https://twitter.com/rdpeng Hilary on Twitter: https://twitter.com/hspter Get the Not So Standard Deviations book: https://leanpub.com/conversationsondatascience/ Subscribe to the podcast on Apple Podcasts: https://itunes.apple.com/us/podcast/not-so-standard-deviations/id1040614570 Subscribe to the podcast on Google Play: https://play.google.com/music/listen?u=0#/ps/Izfnbx6tlruojkfrvhjfdj3nmna Find past episodes: http://nssdeviations.com Contact us at nssdeviations@gmail.com  

This week's episode is just in time for JupyterCon in NYC, August 22-25... Jupyter notebooks are probably familiar to a lot of data nerds out there as a great open-source tool for exploring data, doing quick visualizations, and packaging code snippets with explanations for sharing your work with others. If you're not a data person, or you are but you haven't tried out Jupyter notebooks yet, here's your nudge to go give them a try. In this episode we'll go back to the old days, before notebooks, and talk about all the ways that data scientists like to work that wasn't particularly well-suited to the command line + text editor setup, and talk about how notebooks have evolved over their lifetime to become even more powerful and well-suited to the data scientist's workflow.

The O’Reilly Programming Podcast: The next technological evolution of cloud systems.In this episode of the O’Reilly Programming Podcast, I talk serverless architecture with Mike Roberts, engineering leader and co-founder of Symphonia, a serverless and cloud architecture consultancy. Roberts will give two presentations—Serverless Architectures: What, Why, Why Not, and Where Next? and Designing Serverless AWS Applications—at the O’Reilly Software Architecture Conference, October 16-19, 2017, in London.Discussion points: Why Roberts calls serverless “the next evolution of cloud systems,” as individual process deployment and the resource allocation of servers are increasingly outsourced to vendors How serverless architectures use backend-as-a-service (BaaS) products and functions-as-a-service (FaaS) platforms The similarities and differences between a serverless architecture and microservices, and how microservices ideas can be applied to serverless Roberts explains that serverless is “not an all-or-nothing approach,” and that often “the best architecture for a company is going to be a hybrid architecture between serverless and non-serverless technologies.” Recent advances in serverless tooling, including progress in distributed system monitoring tools, such as Amazon’s X-Ray We also get a preview of JupyterCon, August 22-25, 2017, in New York, from conference co-chair Fernando Perez. Our discussion highlights the sessions on JupyterLab, and the UC Berkeley Data Science program, an introductory-level course in which the students use Jupyter Notebooks. Other links: Video of Roberts’ presentation An Introduction to Serverless at the April 2017 Software Architecture in New York The free eBook What Is Serverless?, by Mike Roberts and John Chapin The video AWS Lambda, presented by Mike Roberts and John Chapin Video of Roberts and Chapin’s OSCON 2017 presentation Building, Displaying and Running a Scalable and Extensible Serverless Application Using AWS Sam Newman’s book Building Microservices

The O’Reilly Programming Podcast: The next technological evolution of cloud systems.In this episode of the O’Reilly Programming Podcast, I talk serverless architecture with Mike Roberts, engineering leader and co-founder of Symphonia, a serverless and cloud architecture consultancy. Roberts will give two presentations—Serverless Architectures: What, Why, Why Not, and Where Next? and Designing Serverless AWS Applications—at the O’Reilly Software Architecture Conference, October 16-19, 2017, in London.Discussion points: Why Roberts calls serverless “the next evolution of cloud systems,” as individual process deployment and the resource allocation of servers are increasingly outsourced to vendors How serverless architectures use backend-as-a-service (BaaS) products and functions-as-a-service (FaaS) platforms The similarities and differences between a serverless architecture and microservices, and how microservices ideas can be applied to serverless Roberts explains that serverless is “not an all-or-nothing approach,” and that often “the best architecture for a company is going to be a hybrid architecture between serverless and non-serverless technologies.” Recent advances in serverless tooling, including progress in distributed system monitoring tools, such as Amazon’s X-Ray We also get a preview of JupyterCon, August 22-25, 2017, in New York, from conference co-chair Fernando Perez. Our discussion highlights the sessions on JupyterLab, and the UC Berkeley Data Science program, an introductory-level course in which the students use Jupyter Notebooks. Other links: Video of Roberts’ presentation An Introduction to Serverless at the April 2017 Software Architecture in New York The free eBook What Is Serverless?, by Mike Roberts and John Chapin The video AWS Lambda, presented by Mike Roberts and John Chapin Video of Roberts and Chapin’s OSCON 2017 presentation Building, Displaying and Running a Scalable and Extensible Serverless Application Using AWS Sam Newman’s book Building Microservices

In this special sponsored episode, Chris talks with Paco Nathan about JupyterCon.