POPULARITY
Categories
What happens when precarious urban cultural laborers take data collection, laws, and policymaking into their own hands? Buskers have been part of our cities for hundreds of years, but they remain invisible to governments and in datasets. From nuisance to public art, this cultural practice can help us understand the politics of data collection, archives, regulatory frameworks, and urban planning. Busking also responds to underlying questions on the boundaries of the rights to the city, and who has a voice in shaping how our cities are planned and governed.A transnational exploration of street performance, Urban Music Governance examines the intricate limits of legality, data visibility, and resistance from the perspective of those working at the social and regulatory margins of society. Based on a decade of fieldwork in Rio de Janeiro and Montreal, this book offers a lively account of why such an often-overlooked practice matters today.By investigating the role of busking in contemporary society, Urban Music Governance presents an original interdisciplinary study that exposes how power dynamics in policymaking decide issues of access—and exclusion—around us, above and below ground. Jess Reia is an Assistant Professor of Data Science at the University of Virginia, USA, working on data justice, technology policy, and urban governance. Alex Hallbom is a Registered Professional Planner in British Columbia, Canada. He sits on the editorial board of Plan Canada, the professional publication for planners in Canada. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/anthropology
What happens when precarious urban cultural laborers take data collection, laws, and policymaking into their own hands? Buskers have been part of our cities for hundreds of years, but they remain invisible to governments and in datasets. From nuisance to public art, this cultural practice can help us understand the politics of data collection, archives, regulatory frameworks, and urban planning. Busking also responds to underlying questions on the boundaries of the rights to the city, and who has a voice in shaping how our cities are planned and governed.A transnational exploration of street performance, Urban Music Governance examines the intricate limits of legality, data visibility, and resistance from the perspective of those working at the social and regulatory margins of society. Based on a decade of fieldwork in Rio de Janeiro and Montreal, this book offers a lively account of why such an often-overlooked practice matters today.By investigating the role of busking in contemporary society, Urban Music Governance presents an original interdisciplinary study that exposes how power dynamics in policymaking decide issues of access—and exclusion—around us, above and below ground. Jess Reia is an Assistant Professor of Data Science at the University of Virginia, USA, working on data justice, technology policy, and urban governance. Alex Hallbom is a Registered Professional Planner in British Columbia, Canada. He sits on the editorial board of Plan Canada, the professional publication for planners in Canada. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/sociology
What happens when precarious urban cultural laborers take data collection, laws, and policymaking into their own hands? Buskers have been part of our cities for hundreds of years, but they remain invisible to governments and in datasets. From nuisance to public art, this cultural practice can help us understand the politics of data collection, archives, regulatory frameworks, and urban planning. Busking also responds to underlying questions on the boundaries of the rights to the city, and who has a voice in shaping how our cities are planned and governed.A transnational exploration of street performance, Urban Music Governance examines the intricate limits of legality, data visibility, and resistance from the perspective of those working at the social and regulatory margins of society. Based on a decade of fieldwork in Rio de Janeiro and Montreal, this book offers a lively account of why such an often-overlooked practice matters today.By investigating the role of busking in contemporary society, Urban Music Governance presents an original interdisciplinary study that exposes how power dynamics in policymaking decide issues of access—and exclusion—around us, above and below ground. Jess Reia is an Assistant Professor of Data Science at the University of Virginia, USA, working on data justice, technology policy, and urban governance. Alex Hallbom is a Registered Professional Planner in British Columbia, Canada. He sits on the editorial board of Plan Canada, the professional publication for planners in Canada. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/public-policy
Investor Fuel Real Estate Investing Mastermind - Audio Version
In this episode of the Real Estate Pro Show, host Erika interviews Adam Eldibany founder of Home Builder, who shares his journey from data science to real estate financing. Adam discusses the evolution of his company, the challenges of data quality in real estate, and the importance of relationships in the industry. He also shares success stories from clients and offers advice for new investors, emphasizing the impact of technology on the future of real estate financing. Professional Real Estate Investors - How we can help you: Investor Fuel Mastermind: Learn more about the Investor Fuel Mastermind, including 100% deal financing, massive discounts from vendors and sponsors you're already using, our world class community of over 150 members, and SO much more here: http://www.investorfuel.com/apply Investor Machine Marketing Partnership: Are you looking for consistent, high quality lead generation? Investor Machine is America's #1 lead generation service professional investors. Investor Machine provides true ‘white glove' support to help you build the perfect marketing plan, then we'll execute it for you…talking and working together on an ongoing basis to help you hit YOUR goals! Learn more here: http://www.investormachine.com Coaching with Mike Hambright: Interested in 1 on 1 coaching with Mike Hambright? Mike coaches entrepreneurs looking to level up, build coaching or service based businesses (Mike runs multiple 7 and 8 figure a year businesses), building a coaching program and more. Learn more here: https://investorfuel.com/coachingwithmike Attend a Vacation/Mastermind Retreat with Mike Hambright: Interested in joining a “mini-mastermind” with Mike and his private clients on an upcoming “Retreat”, either at locations like Cabo San Lucas, Napa, Park City ski trip, Yellowstone, or even at Mike's East Texas “Big H Ranch”? Learn more here: http://www.investorfuel.com/retreat Property Insurance: Join the largest and most investor friendly property insurance provider in 2 minutes. Free to join, and insure all your flips and rentals within minutes! There is NO easier insurance provider on the planet (turn insurance on or off in 1 minute without talking to anyone!), and there's no 15-30% agent mark up through this platform! Register here: https://myinvestorinsurance.com/ New Real Estate Investors - How we can work together: Investor Fuel Club (Coaching and Deal Partner Community): Looking to kickstart your real estate investing career? Join our one of a kind Coaching Community, Investor Fuel Club, where you'll get trained by some of the best real estate investors in America, and partner with them on deals! You don't need $ for deals…we'll partner with you and hold your hand along the way! Learn More here: http://www.investorfuel.com/club —--------------------
Digital Health Canada's Setting the Winning Conditions for AI-powered Healthcare report summarizes actionable nsights from interviews eight leading health care organizations implementing AI. In this episode, we dive into those conditions and their implications - learning what sets winning AI implementations apart. Guests: Muhammad Mamdani, Vice President of Data Science and Advanced Analytics, Unity Health Toronto Ted Scott, Vice President Innovation and Partnerships, Hamilton Health Sciences Learn More: Setting the Winning Conditions for AI-Powered Healthcare (report) Unity Health Toronto Hamilton Health Sciences Episode Summary 01:16 Meet the Experts: Career Journeys 03:00 Challenges in Health Care: From Theory to Practice 08:55 Data Challenges and Privacy Concerns 13:08 Building Trust and Equity in Healthcare 20:11 Defining Value in Healthcare 24:37 Evaluating and Scaling AI Solutions 27:42 Future of AI in Canadian Health Care 29:40 Advice for AI Adoption in Healthcare 35:14 Final Thoughts and Reflections Music: RetroFuture Clean and Breakdown, by Kevin MacLeod. Used under Creative Commons.
The rise of Artificial Intelligence ignites age-old questions about ethics, responsibility, and the nature of decision-making. As AI systems become more embedded in daily life, shaping what we see, buy, and believe, the call for "Ethical AI" grows louder. But what does that really mean? Is it about aligning machine behavior with human values? Can reasonable professionals agree on a set of standards to safely shepherd business into the AI Epoch? Register for this special two-hour DM Radio to find out! Host @eric_kavanagh will interview several industry luminaries, including: Andy Hannah, Founder of Blue Street Data, and Chairperson for the University of Pittsburgh's Responsible AI Advisory Board. Also joining will be Michael Colaresi, Associate Vice Provost for Data Science at the University of Pittsburgh. Another expert on the call will be Jessica Talisman, who draws on her background in library and information science to champion structured, ethical AI systems. Rounding out the panel will be Mench.ai Founder, Nikolai Mentchoukov, who created AI Agents before that name was even born!
Get a "Heck Yes" with Carissa Woo Wedding Photographer and Coach
In today's episode, I'm joined by Brandon Wong — the CEO and Founder of Demystify AI, an innovative AI company based in Los Angeles. Brandon grew up in Southern California, graduated from UCLA with a degree in Data Science (specializing in Cybersecurity), and formerly worked as a Senior Software Engineer for the Oscars in Hollywood.
Topics covered in this episode: * Distributed sqlite follow up: Turso and Litestream* * PEP 792 – Project status markers in the simple index* Run coverage on tests docker2exe: Convert a Docker image to an executable Extras Joke Watch on YouTube About the show Sponsored by Digital Ocean: pythonbytes.fm/digitalocean-gen-ai Use code DO4BYTES and get $200 in free credit Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: Distributed sqlite follow up: Turso and Litestream Michael Booth: Turso marries the familiarity and simplicity of SQLite with modern, scalable, and distributed features. Seems to me that Turso is to SQLite what MotherDuck is to DuckDB. Mike Fiedler Continue to use the SQLite you love and care about (even the one inside Python runtime) and launch a daemon that watches the db for changes and replicates changes to an S3-type object store. Deeper dive: Litestream: Revamped Brian #2: PEP 792 – Project status markers in the simple index Currently 3 status markers for packages Trove Classifier status Indices can be yanked PyPI projects - admins can quarantine a project, owners can archive a project Proposal is to have something that can have only one state active archived quarantined deprecated This has been Approved, but not Implemented yet. Brian #3: Run coverage on tests Hugo van Kemenade And apparently, run Ruff with at least F811 turned on Helps with copy/paste/modify mistakes, but also subtler bugs like consumed generators being reused. Michael #4: docker2exe: Convert a Docker image to an executable This tool can be used to convert a Docker image to an executable that you can send to your friends. Build with a simple command: $ docker2exe --name alpine --image alpine:3.9 Requires docker on the client device Probably doesn't map volumes/ports/etc, though could potentially be exposed in the dockerfile. Extras Brian: Back catalog of Test & Code is now on YouTube under @TestAndCodePodcast So far 106 of 234 episodes are up. The rest are going up according to daily limits. Ordering is rather chaotic, according to upload time, not release ordering. There will be a new episode this week pytest-django with Adam Johnson Joke: If programmers were doctors
Compensation isn't just an HR function—it's a core business strategy. In this episode of Comp and Coffee, we look into the pay crystal ball with Rebecca Toman of Pearl Meyer, Ruth Thomas, Chief Compensation Strategist at Payscale, and Sara Hillenmeyer, Payscale's Director of Data Science. Together, they explore how trusted data, AI, and a forward-thinking approach to comp strategy can help organizations not just keep up—but lead. If you care about performance, retention, equity, or executive pay, this episode is your blueprint for aligning comp strategy with long-term business success.
Talk Python To Me - Python conversations for passionate developers
Every year the core developers of Python convene in person to focus on high priority topics for CPython and beyond. This year they met at PyCon US 2025. Those meetings are closed door to keep focused and productive. But we're lucky that Seth Michael Larson was in attendance and wrote up each topic presented and the reactions and feedback to each. We'll be exploring this year's Language Summit with Seth. It's quite insightful to where Python is going and the pressing matters. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Sentry AI Monitoring, Code TALKPYTHON Talk Python Courses Links from the show Seth on Mastodon: @sethmlarson@fosstodon.org Seth on Twitter: @sethmlarson Seth on Github: github.com Python Language Summit 2025: pyfound.blogspot.com WheelNext: wheelnext.dev Free-Threaded Wheels: hugovk.github.io Free-Threaded Python Compatibility Tracking: py-free-threading.github.io PEP 779: Criteria for supported status for free-threaded Python: discuss.python.org PyPI Data: py-code.org Senior Engineer tries Vibe Coding: youtube.com Watch this episode on YouTube: youtube.com Episode #514 deep-dive: talkpython.fm/514 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy
We're in the midst of summer and we know that power outages can happen more frequently during this season due to higher temperatures and an increased demand for electricity. A couple years ago we sat down with Ram Rajagopal, an expert in the future of electrical power. He shared a few ways our existing system of massive power plants is slowly but surely giving way to a much leaner, decentralized system of small-scale power generation. Ram refers to this as a move from an “infrastructure-centric” model to a “human-centric” grid — one that will be much smarter, more inclusive and better able to adapt to the needs of individual users. It's a topic that impacts all of us and we hope you'll tune in again for a refresher on how the electric grid works and how it's evolving.Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to thefutureofeverything@stanford.edu.Episode Reference Links:Stanford Profile: Ram RajagopalConnect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>> Twitter/X / Instagram / LinkedIn / FacebookChapters:(00:00:00) IntroductionRuss Altman introduces guest Ram Rajagopal, a professor of engineering at Stanford University.(00:03:47) What is Powernet?Outline of Powernet—a decentralized, user-focused power grid vision.(00:05:34) Behind-the-Meter IntelligenceAiming to align supply and demand by understanding consumer needs.(00:07:58) Smart Dimmers & Data PrivacyBalancing energy efficiency with privacy concerns in home automation.(00:10:05) Aggregators & Local ControlFuture energy sharing may rely on local devices and trusted middlemen.(00:11:50) Human Motivation & Energy BehaviorWhy both ethics and cost will drive user participation in energy decisions.(00:14:02) Teaching Energy AwarenessA program teaching middle-schoolers to analyze home energy use.(00:16:17) Automating Energy UseBehavioral and systems changes to help align wellness with grid needs.(00:18:58) Grid Shift: Renewables & StorageHow evolving the grid demands real-time monitoring and local resilience.(00:19:57) Sensors & Operational SafetyThe sensing technology that ensures transformers and lines stay within limits.(00:21:27) Smart Dairy: Cooling Cows with AIHow smart fans and storage reduced a dairy farm's energy output.(00:23:28) Building Trust with FarmersThe collaborative process behind deploying the grid tech at the farm.(00:25:01) Smart Ventilation at ScaleScaling the ventilation tech tested on farms to improve public health spaces.(00:26:06) Equity in the Human-Centered GridHow price signals risk overburdening the most vulnerable communities.(00:28:22) Conclusion Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook
In this episode, we're joined by Jackie (@agaperste), Head of Data Science at Uniswap Foundation, and Grace (@grace_lily), part of the Data team at Uniswap
Hablamos de tecnología e IA con Xavier Ferràs, profesor del departamento de Operaciones, Innovación y Data Science en ESADE. Tertulia con Francisco Navarro, profesor del Instituto de Empresa; Rubén García-Quismondo, Socio Director de Quabbala, Abogados y Economistas; y Gonzalo Garnica, consultor empresarial y editor.
Recebemos o Daniel Romeiro — mais conhecido como Infoslack — para mergulhar de cabeça no universo em ebulição de Inteligência Artificial, DevOps e Machine Learning. Neste episódio, exploramos como filtrar o ruído do hype com uma abordagem de filtro reverso e discutimos os bastidores do deploy de modelos de Machine Learning em produção.Trocamos experiências sobre observabilidade avançada em pipelines de IA e compartilhamos insights sobre como acumular habilidades DevOps ao longo da carreira, sem jamais perder o pé no chão. Entre uma piada e outra, analisamos também o impacto dos testes A/B em tempo real e a complexidade de gerenciar artefatos de IA em escala.Por fim, refletimos sobre as perspectivas futuras: qual será o próximo grande passo para SREs que querem continuar relevantes em um cenário dominado por IA generativa? Nós conversamos sobre como arquiteturas mal planejadas podem se tornar gargalos de latência e apresentamos estratégias para garantir alta disponibilidade mesmo quando as APIs externas decidem ficar fora do ar.Links Importantes:- Daniel Romeiro - https://www.linkedin.com/in/infoslack/- João Brito - https://www.linkedin.com/in/juniorjbn- Assista ao FilmeTEArapia - https://youtu.be/M4QFmW_HZh0?si=HIXBDWZJ8yPbpflMParticipe de nosso programa de acesso antecipado e tenha um ambiente mais seguro em instantes!https://getup.io/zerocveO Kubicast é uma produção da Getup, empresa especialista em Kubernetes e projetos open source para Kubernetes. Os episódios do podcast estão nas principais plataformas de áudio digital e no YouTube.com/@getupcloud.
Social media algorithms silently shape what billions of people see and how they interact online. While most data scientists work to optimize business value within platform rules, there's valuable knowledge to be gained from understanding how these systems can be exploited - knowledge that can make ethical data scientists better at their jobs.In this episode, Tim O'Hearn joins Dr. Genevieve Hayes to share insights from his experience manipulating social media platforms, revealing what ethical data scientists can learn from understanding the dark side of algorithmic systems.This conversation reveals:How social media platforms are essentially just sophisticated recommendation engines [08:16]The "canary" technique for detecting when underlying systems have changed [11:36]Why customer accounts often provide better testing data than artificial test accounts [13:56]The importance of time series data collection for identifying suspicious patterns, effectiveness of campaigns, and understanding platform dynamics [18:04]Guest BioTim O'Hearn is a software engineer who spent years gaining millions of followers for clients by circumventing anti-botting measures on social networks. He is also the author of the new book, Framed: A Villain's Perspective on Social Media.LinksTim's WebsiteConnect with Tim on LinkedInSubscribe to Tim's newsletterConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE
Topics covered in this episode: * Switching to direnv, Starship, and uv* * rqlite - Distributed SQLite DB* * Some Markdown Stuff* Extras Joke Watch on YouTube About the show Sponsored by PropelAuth: pythonbytes.fm/propelauth77 Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: Switching to direnv, Starship, and uv Last week I mentioned that I'm ready to try direnv again, but secretly, I still had some worries about the process. Thankfully, Trey has a tutorial to walk me past the troublesome parts. direnv - an extension for your shell. It augments existing shells with a new feature that can load and unload environment variables depending on the current directory. Switching from virtualenvwrapper to direnv, Starship, and uv - Trey Hunner** Trey has solved a bunch of the problems I had when I tried direnv before Show the virtual environment name in the prompt Place new virtual environments in local .venv instead of in .direnv/python3.12 Silence all of the “loading”, “unloading” statements every time you enter a directory Have a script called venv to create an environment, activate it, create a .envrc file I'm more used to a create script, so I'll stick with that name and Trey's contents A workon script to be able to switch around to different projects. This is a carry over from “virtualenvwrapper', but seems cool. I'll take it. Adding uv to the mix for creating virtual environments. Interestingly including --seed which, for one, installs pip in the new environment. (Some tools need it, even if you don't) Starship Trey also has some setup for Starship. But I'll get through the above first, then MAYBE try Starship again. Some motivation Trey's setup is pretty simple. Maybe I was trying to get too fancy before Starship config in toml files that can be loaded with direnv and be different for different projects. Neato Also, Trey mentions his dotfiles repo. This is a cool idea that I've been meaning to do for a long time. See also: It's Terminal - Bootstrapping With Starship, Just, Direnv, and UV - Mario Munoz Michael #2: rqlite - Distributed SQLite DB via themlu, thanks! rqlite is a lightweight, user-friendly, distributed relational database built on SQLite. Built on SQLite, the world's most popular database Supports full-text search, Vector Search, and JSON documents Access controls and encryption for secure deployments Michael #3: A Python dict that can report which keys you did not use by Peter Bengtsson Very cool for testing that a dictionary has been used as expected (e.g. all data has been sent out via an API or report). Note: It does NOT track d.get(), but it's easy to just add it to the class in the post. Maybe someone should polish it up and put it on pypi (that person is not me :) ). Brian #4: Some Markdown Stuff Textual 4.0.0 adds Markdown.append which can be used to efficiently stream markdown content The reason for the major bump is due to an interface change to Widget.anchor Refreshing to see a symantic change cause a major version bump. html-to-markdown Converts html to markdown A complete rewrite fork of markdownify Lots of fun features like “streaming support” Curious if it can stream to Textual's Markdown.append method. hmmm. Joke: Vibecon is hard to attend
This is episode 298 recorded on July 9th, 2025, where John & Jason talk the Microsoft Fabric June 2025 Feature Summary including lots of Notebook updates in Data Engineering, lower cost for AI functions in Data Science, Copilot for RTI dashboards, and more. For show notes please visit www.bifocal.show
Talk Python To Me - Python conversations for passionate developers
Why do people list to this podcast? Sure, they're looking for technical explorations of new libraries and ideas. But often it's to hear the story behind them. If that speaks to you, then I have the perfect episode lined up. I have Barry Warsaw, Paul Everitt, Carol Willing, and Brett Cannon all back on the show to share stories from the history of Python. You'll hear about how import this came to be and how the first PyCon had around 30 attendees (two of whom are guests on this episode!). Sit back and enjoy the humorous stories from Python's past. Episode sponsors Posit Agntcy Talk Python Courses Links from the show Barry's Zen of Python song: youtube.com Jake Vanderplas - Keynote - PyCon 2017: youtube.com Why it's called “Python” (Monty Python fan-reference): geeksforgeeks.org import antigravity: python-history.blogspot.com NIST Python Workshop Attendees: legacy.python.org Paul Everitt open-sources Zope: old.zope.dev Carol Willing wins ACM Software System Award: awards.acm.org Watch this episode on YouTube: youtube.com Episode #513 deep-dive: talkpython.fm/513 Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy
In this conversation, we explore AI bias, transformative justice, and the future of technology with Dr. Avriel Epps, computational social scientist, Civic Science Postdoctoral Fellow at Cornell University's CATLab, and co-founder of AI for Abolition.What makes this conversation unique is how it begins with Avriel's recently published children's book, A Kids Book About AI Bias (Penguin Random House), designed for ages 5-9. As an accomplished researcher with a PhD from Harvard and expertise in how algorithmic systems impact identity development, Avriel has taken on the remarkable challenge of translating complex technical concepts about AI bias into accessible language for the youngest learners.Key themes we explore:- The Translation Challenge: How to distill graduate-level research on algorithmic bias into concepts a six-year-old can understand—and why kids' unfiltered responses to AI bias reveal truths adults often struggle to articulate- Critical Digital Literacy: Why building awareness of AI bias early can serve as a protective mechanism for young people who will be most vulnerable to these systems- AI for Abolition: Avriel's nonprofit work building community power around AI, including developing open-source tools like "Repair" for transformative and restorative justice practitioners- The Incentive Problem: Why the fundamental issue isn't the technology itself, but the economic structures driving AI development—and how communities might reclaim agency over systems built from their own data- Generational Perspectives: How different generations approach digital activism, from Gen Z's innovative but potentially ephemeral protest methods to what Gen Alpha might bring to technological resistanceThroughout our conversation, Avriel demonstrates how critical analysis of technology can coexist with practical hope. Her work embodies the belief that while AI currently reinforces existing inequalities, it doesn't have to—if we can change who controls its development and deployment.The conversation concludes with Avriel's ongoing research into how algorithmic systems shaped public discourse around major social and political events, and their vision for "small tech" solutions that serve communities rather than extracting from them.For anyone interested in AI ethics, youth development, or the intersection of technology and social justice, this conversation offers both rigorous analysis and genuine optimism about what's possible when we center equity in technological development.About Dr. Avriel Epps:Dr. Avriel Epps (she/they) is a computational social scientist and a Civic Science Postdoctoral Fellow at the Cornell University CATLab. She completed her Ph.D. at Harvard University in Education with a concentration in Human Development. She also holds an S.M. in Data Science from Harvard's School of Engineering and Applied Sciences and a B.A. in Communication Studies from UCLA. Previously a Ford Foundation predoctoral fellow, Avriel is currently a Fellow at The National Center on Race and Digital Justice, a Roddenberry Fellow, and a Public Voices Fellow on Technology in the Public Interest with the Op-Ed Project in partnership with the MacArthur Foundation.Avriel is also the co-founder of AI4Abolition, a community organization dedicated to increasing AI literacy in marginalized communities and building community power with and around data-driven technologies. Avriel has been invited to speak at various venues including tech giants like Google and TikTok, and for The U.S. Courts, focusing on algorithmic bias and fairness. In the Fall of 2025, she will begin her tenure as Assistant Professor of Fair and Responsible Data Science at Rutgers University.Links:- Dr. Epps' official website: https://www.avrielepps.com- AI for Abolition: https://www.ai4.org- A Kids Book About AI Bias details: https://www.avrielepps.com/book
Listen as an experienced post -secondary professor and Dean of Computing and Data Science shares her insights as she assumes the position of the Head of School at a 6-12 independent school, the New England Innovation Academy. Dr. Durga Suresh-Menon provides a definition of innovation and discusses the need for curriculum and instruction to be continuously relevant. How do students prepare for what comes next? How do staff engage in the learning that supports their work with student? Email Dr. Suresh-Menon: durga.suresh-menon@neiacademy.org Learn more about the New England Innovation Academy here. Subscribe to the Steve Barkley Ponders Out Loud podcast on iTunes or visit BarkleyPD.com to find new episodes!
Most dashboards and reports get ignored despite all the technical expertise that goes into creating them. The reason isn't technical limitations or poor data quality - it's that they fail to deliver value to the people who are supposed to use them.In this Value Boost episode, Nicholas Kelly joins Dr. Genevieve Hayes to reveal proven strategies for increasing dashboard adoption and showcasing your value as a data professional.In this episode, you'll discover:The number one reason why dashboards fail [01:15]The three-bucket framework that transforms dashboard development [04:06]How to salvage an already-built dashboard [07:12]The simple wireframing technique that opens doors to meaningful user conversations [10:08]Guest BioNicholas Kelly is the founder of Delivering Data Analytics, a consultancy focused on helping organisations enable their teams to make smarter, faster, and more confident decisions through data and AI. He is also the author of Delivering Data Analytics and the recently released How to Interpret Data.LinksNicholas's WebsiteConnect with Nicholas on LinkedInConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE
All companies start small. The lucky ones grow, and growth necessarily comes with change. This month on the Klaviyo Data Science Podcast, we look at Klaviyo's growth through the past 8 years and the profound effects that growth has had on R&D, ranging from the tooling we use to the processes we employ to the very culture we strive to cultivate. Listen in to learn:How the day-to-day of some of our most senior engineers has changedWhy common headaches like planning, deployment, and cross-team coordination can get harder as your org grows — and why they can get easier What a single lunch can teach you about a company's culture For more details, check out the full writeup on Medium!
In this insightful episode of IDEA Collider, Mike welcomes Mathai Mammen, Chairman and CEO of Parabilis Medicines. Mathai shares his extensive journey through academia, MD PhD program at Harvard, co-founding Theravance, and leadership roles at Merck and J&J. They delve into Mathai's innovative approach to creating transformative medicines, navigating the biotech industry, and the unique challenges of targeting 'undruggable' proteins. They also discuss the role of AI in drug discovery, the importance of strategic risk, and fostering team resilience and spirit in both large and small pharma companies. 00:00 Introduction and Guest Background00:56 Founding Thebans and Career Highlights01:43 Leadership at Merck and J&J02:18 Innovative Approaches at Parabilis Medicines04:09 Defining and Tackling Undruggable Targets09:27 Multivalent Drug Design and Bispecifics13:53 AI and Data Science in Drug Development19:28 Building and Leading World-Class Teams25:41 The Importance of Holding Conviction as an Entrepreneur26:25 Learning from Setbacks in the Biotech Industry30:10 Challenges and Innovations in Drug Development32:28 Navigating the Ups and Downs of the Biotech Industry36:02 The Mission and Future of Parabilis40:35 Personal Reflections and Advice for Entrepreneurs46:46 Book Recommendations and Closing Thoughts Don't forget to Like, Share, Subscribe, Rate, and Review! Keep up with Mathai Mammen;LinkedIn: https://www.linkedin.com/in/mathai-mammen/Website: https://parabilismed.com/ Follow Mike Rea On;Website: https://www.ideapharma.com/X: https://x.com/ideapharmaLinkedIn: https://www.linkedin.com/in/bigidea/ Listen to more fantastic podcast episodes: https://podcast.ideapharma.com/
Tired of spending money on data courses you never finish? Here are 7 essential books that will actually boost your analytical skills, with no subscription required! Plus, make sure to tune in till the end as one lucky listener will get a free book from this list! Get the books here!DISCLAIMER: Some of the links in this video are affiliate links, meaning if you click through and make a purchase, I may earn a commission at no extra cost to you.Storytelling with Data by Cole Nussbaumer Knaflic
AI - two little letters that we seemingly can't escape. AI is upending not only our professional lives but also our personal, everyday lives.
With Artificial Intelligence (AI) becoming increasingly prominent in our everyday lives, discussions have begun on whether it should be taught in schools. In this podcast, we speak to Abhinav Dhall, Associate Professor in the Department of Data Science and AI at Monash University, to explore whether introducing AI in classrooms would prepare the next generation for the future or hinder their critical thinking skills.
Topics covered in this episode: * ty documentation site and uv migration guide* * uv build backend is now stable + other Astral news* * Refactoring long boolean expressions* * fastapi-ml-skeleton* Extras Joke Watch on YouTube About the show Sponsored by Sentry: pythonbytes.fm/sentry Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: ty documentation site and uv migration guide via Skyler Kasko Astral created a documentation site for ty (PR #744 in release 0.0.1-alpha.13). Astral added a page on migrating from pip to a uv project in the uv documentation. (PR #12382 in release 0.7.19). Talk Python episode on ty. Brian #2: uv build backend is now stable + other Astral news The uv build backend is now stable Tim Hopper via Python Developer Tooling Handbook From Charlie Marsh “The uv build backend is now stable, and considered ready for production use. An alternative to setuptools, hatchling, etc. for pure Python projects, with a focus on good defaults, user-friendly error messages, and performance. When used with uv, it's 10-35x faster.” “(In a future release, we'll make this the default.)” [build-system] requires = ["uv_build>=0.7.19,
From the viral article "Tech's Dumbest Mistake: Why Firing Programmers for AI Will Destroy Everything" on my newsletter at https://defragzone.substack.com/p/techs-dumbest-mistake-why-firing here are my thoughts about AI replacing programmers...
Hollister Incorporated, a global leader in ostomy, continence, wound care and critical care products has announced an €80m R&D investment and a digital transformation project that will create approximately 50 new jobs in Ballina. The multimillion-euro investment aims to elevate Ballina into a global epicentre of expertise through novel device design and extensive site-wide training, setting a benchmark for digital transformation within Hollister's global network. This project is supported by the Irish Government through IDA Ireland. Minister for Social Protection and Minister for Rural and Community Development and the Gaeltacht Dara Calleary TD said: "This is a terrific day for Ballina and North Mayo with the announcement of 50 additional jobs for the region. Hollister is more than just a manufacturing plant in Ballina; it is one of the mainstays of our community. Today, second and third generations of families are employed there boosting the local economy and contributing to the everyday life of the town. I want to pay credit to Shane Caher and all of the staff in Hollister who have dedicated themselves to Ballina and to the West of Ireland but also to all of the past Hollister management and staff who's work, and commitment is the foundation of the plant's success today. Finally, I would like to acknowledge IDA Ireland for their continued support to Hollister and across Mayo. I very much look forward to what the next 50 years will bring for Hollister and Ballina" Minister of State at the Department of Enterprise, Tourism and Employment, Alan Dillon TD, said: "This €80 million investment by Hollister Inc. is very welcome news. It is a powerful endorsement of Ballina's skilled workforce and Ireland's reputation as a hub for innovation in healthcare manufacturing. To see a long-standing employer, like Hollister, continue to grow and evolve through cutting-edge research and digital transformation is very encouraging. The creation of 50 new high-quality jobs will also bring economic and social benefits to the region. On behalf of the Irish Government, I thank Hollister for its continued commitment to Ballina and the West of Ireland, and I wish the team there the very best for the future and many more years of success here in Co. Mayo." Founded in 1921 in Illinois, the US MedTech manufacturer has been part of the fabric of Ballina since 1976, where it now employs almost 1000 people. Hollister is currently recruiting in the areas of Engineering, Data Science and Business Services. To explore opportunities, visit Career Opportunities | Hollister IE. "We are thrilled to announce this significant milestone for Hollister Incorporated. Our commitment to innovation and excellence continues to drive us forward, and this investment in our research program and digital transformation project is a testament to the hard work and dedication of our entire team," said Shane Caher, Senior Director of Plant Operations and General Manager. "We look forward to the exciting opportunities that lie ahead as we continue to deliver on Our Mission to make life more rewarding and dignified for those who use our products and services." IDA Ireland CEO Michael Lohan said: "Since 1976, Hollister has been creating jobs and investment in Co. Mayo. In the intervening near 50 years, Hollister has again and again committed to and delivered on its ambitions for its Irish operations. Supporting Hollister and companies across IDA Ireland's client portfolio with R&D investment and digital transformation endeavours sits right at the heart of Adapt Intelligently: A Strategy for Sustainable Growth and Innovation 2025-29. I wish to congratulate Hollister and assure them of IDA Ireland's continued support." More about Irish Tech News Irish Tech News are Ireland's No. 1 Online Tech Publication and often Ireland's No.1 Tech Podcast too. You can find hundreds of fantastic previous episodes and subscribe using whatever platform you like via our Anchor.fm page here: https://...
Was passiert eigentlich, wenn modernste KI auf einen der geheimnisvollsten Arbeitgeber Deutschlands trifft?
This week Dr. Nadine Choueiter of Mount Sinai hosts a special episode of Pediheart: Pediatric Cardiology Today in which we speak with emeritus Professor of Pediatrics at the University of Toronto, Dr. Brian McCrindle about his career and life. How did he develop a love of pediatric cardiology? Who were some of his early mentors? How did he develop the international Kawasaki Disease Registry and how has he cultivated it despite minimal funding? How did he develop an interest in preventive cardiology? How can a young person make their clinical work also their academic work? Dr. McCrindle also shares some insights into navigating a successful life as well as retirement. This is a rare opportunity to be inspired by one of the great pediatric cardovascular researchers of the past 3 decades.
Como é manter o motor de dados de uma dos maiores grupos de varejo do Brasil rodando sem parar — enquanto se experimenta tecnologias de IA Generativa que poucas empresas do mundo ousaram colocar em produção?Neste episódio especial, convidamos Lucas Eduardo Wichinevsky, Rodrigo Lucchesi e Marcelle Araujo Chiriboga Carvalho do Grupo Boticário, para abrir a caixa-preta da Engenharia de Machine Learning.Lembrando que você pode encontrar todos os podcasts da comunidade Data Hackers no Spotify, iTunes, Google Podcast, Castbox e muitas outras plataformas.Falamos no episódio:Marcelle Chiriboga - Gerente de Data Science de Lojas e Franquias no Grupo BoticárioLucas Eduardo Wichinevsky - Gerente de Data Science de Tech Corporate no Grupo BoticárioRodrigo Lucchesi - Gerente de Data Science de Demanda e RGM no no Grupo BoticárioNossa Bancada — Data Hackers:Monique Femme — Head of Community Management na Data HackersPaulo Vasconcellos — Co-founder da Data Hackers e Principal Data Scientist na Hotmart
Talk Python To Me - Python conversations for passionate developers
Do you like to dive into the details and intricacies of how Python executes and how we can optimize it? Well, do I have an episode for you. We welcome back Brandt Bucher to give us an update on the upcoming JIT compiler for Python and why it differs from JITs for languages such as C# and Java. Episode sponsors Posit Talk Python Courses Links from the show Brandt Bucher: github.com/brandtbucher PyCon Talk: What they don't tell you about building a JIT compiler for CPython: youtube.com Specializing, Adaptive Interpreter Episode: talkpython.fm Watch this episode on YouTube: youtube.com Episode #512 deep-dive: talkpython.fm/512 Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy
Andrew Ackerman is the Head of REACH Labs at Second Century Ventures, the strategic venture arm of the National Association of Realtors® (NAR). Backed by NAR, SCV invests in early-stage PropTech and construction tech companies, providing them with access to a vast network of real estate professionals and industry expertise. A former entrepreneur, angel investor, and accelerator director at Dreamit Ventures, Andrew has backed 70+ startups and designed structured programs to help founders raise capital and close deals faster. He is also the author of “The Entrepreneur's Odyssey,” a story-driven startup guide, and a frequent contributor to Forbes, Propmodo, and other leading publications.(01:19) – Andrew Ackerman's Journey in PropTech (03:06) – Evolution of the PropTech Landscape (06:40) – The Role of Reach Labs, Second Century Ventures and NAR (10:06) – Challenges in Real Estate Transactions (13:00) – Venture Returns in PropTech (21:01) – Feature: Blueprint - The Future of Real Estate - Register for 2025: The Premier Event for Industry Executives, Real Estate & Construction Tech Startups and VC's, at The Venetian, Las Vegas on Sep. 16th-18th, 2025. (23:03) – Qualifying Investment Opportunities (23:32) – Challenges in Portfolio Construction & Valuation Dilemmas (30:00) – The Role of Venture Debt (35:59) – The Entrepreneur's Odyssey(29:22) - Collaboration Superpower: Richard Nixon
In this episode of TAG Data Talk, Dr. Beverly Wright discusses with Bhavna Mehta , Assistant Vice President at Cincinnati Children's Hospital Medical Center: What are some examples of ways AI technology can support healthcare operations and decision making?Describe some of the challenges specific to healthcare when thinking about leveraging AI.How do you think AI will work with us in the future to support and improve community health?Bhavna Mehta, Senior Manager of Data Science at The Home DepotFollow Bhavna Mehta
In this episode of TAG Data Talk, Dr. Beverly Wright discusses with Huzaifa Sayed, Senior Manager of Data Science at The Home Depot:What are some business operations solvable via AI?How can AI technologies help streamline, improve, or otherwise support operations?What does the future hold for leveraging AI as part of operational activities?What final piece of advice would you give to someone trying to find ways to leverage AI technology used to support business functions?Huzaifa Sayed, Senior Manager of Data Science at The Home DepotFollow Huzaifa Sayed
Despite unprecedented data abundance and widespread data science education, even experienced data professionals still struggle to interpret data effectively. They draw wrong conclusions, miss critical insights, or fail to communicate findings in actionable ways.In this episode, Nicholas Kelly joins Dr. Genevieve Hayes to tackle the critical challenge of data interpretation - revealing why technical expertise alone isn't enough and sharing practical frameworks for transforming raw data into actionable business insights that drive real organisational change.This conversation reveals:The four primary challenges that make data interpretation so difficult [02:24]Why ChatGPT and AI tools are changing the data interpretation landscape [06:23]The "Five Whys" technique that ensures you're asking the right questions instead of wasting time on problems everyone already understands [17:32]Why successful data projects don't end with presenting insights and what to do next [20:01]Guest BioNicholas Kelly is the founder of Delivering Data Analytics, a consultancy focused on helping organisations enable their teams to make smarter, faster, and more confident decisions through data and AI. He is also the author of Delivering Data Analytics and the recently released How to Interpret Data.LinksNicholas's WebsiteConnect with Nicholas on LinkedInConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE
Join host Tiana Zhao, FSA, CERA, as she explores the emerging field of marketing actuaries in this insightful episode of the SOA Marketing and Distribution podcast. Discover how these professionals blend actuarial science with marketing strategies to drive data-informed business decisions. Tiana breaks down the key responsibilities of marketing actuaries, including data analysis, predictive modeling, customer segmentation, and pricing optimization. Learn how this evolving role is shaping the future of marketing in our increasingly data-driven business landscape. Whether you're an actuary looking to expand your skillset or a marketing professional curious about the power of actuarial science, this episode offers valuable insights into this exciting intersection of disciplines.
Most LLM-powered features do not break at the model. They break at the context. So how do you retrieve the right information to get useful results, even under vague or messy user queries? In this episode, we hear from Eric Ma, who leads data science research in the Data Science and AI group at Moderna. He shares what it takes to move beyond toy demos and ship LLM features that actually help people do their jobs. We cover: • How to align retrieval with user intent and why cosine similarity is not the answer • How a dumb YAML-based system outperformed so-called smart retrieval pipelines • Why vague queries like “what is this all about” expose real weaknesses in most systems • When vibe checks are enough and when formal evaluation is worth the effort • How retrieval workflows can evolve alongside your product and user needs If you are building LLM-powered systems and care about how they work, not just whether they work, this one is for you. LINKS Eric's website (https://ericmjl.github.io/) Upcoming Events on Luma (https://lu.ma/calendar/cal-8ImWFDQ3IEIxNWk) Hugo's recent newsletter about upcoming events and more! (https://hugobowne.substack.com/p/stop-building-agents)
Andrew Parnell, Professor of Data Science for Climate at UCD, discusses Europe's extreme heatwave.
Topics covered in this episode: * Python Cheat Sheets from Trey Hunner* * Automatisch* * mureq-typed* * My CLI World* Extras Joke Watch on YouTube About the show Sponsored by Posit: pythonbytes.fm/connect Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: Python Cheat Sheets from Trey Hunner Some fun sheets Python f-string tips & cheat sheets Python's pathlib module Python's many command-line utilities Michael #2: Automatisch Open source Zapier alternative Automatisch helps you to automate your business processes without coding. Use their affordable cloud solution or self-host on your own servers. Automatisch allows you to store your data on your own servers, good for companies dealing with sensitive user data, particularly in industries like healthcare and finance, or those based in Europe bound by General Data Protection Regulation (GDPR). Michael #3: mureq-typed Single file, zero-dependency alternative to requests. Fully typed. Modern Python tooling. Typed version of mureq (covered in 2022 on episode 268) Intended to be vendored in-tree by Linux systems software and other lightweight applications. mureq-typed is a drop-in, fully API compatible replacement for mureq updated with modern Python tooling: Type checked with mypy, ty, and pyrefly. Formatted with black, no ignore rules necessary. Linted with ruff (add these rules for mureq.py to your per-file-ignores). Brian #4: My CLI World Frank Wiles Encouragement to modify your command line environment Some of Franks tools direnv, zoxide, fd, ack, atuin, just Also some aliases, like gitpulllog Notes We covered poethepoet recently, if just just isn't cutting it for you. I tried to ilke starship, bit for some reason with my setup, it slows down the shell too much. Extras Brian: Interesting read of the week: New theory proposes time has three dimensions, with space as a secondary effect Michael's: New quantum theory of gravity brings long-sought 'theory of everything' a crucial step closer Joke: Brian read a few quotes from the book Disappointing Affirmations, by Dave Tarnowski “You are always just a moment away from your next worst day ever. Or your next best day ever, but let's be realistic.” “You can be anything you want. And yet you keep choosing to be you. I admire your dedication to the role.” “Today I am letting go of the things that are holding me back from the life that I want to live. Then I'm picking them all up again because I have separation anxiety.”
Andreas Voniatis, founder of Arteos and author of "Data-Driven SEO with Python," is revolutionizing the SEO landscape by integrating data science and AI into organic growth strategies. He emphasizes the need for businesses, particularly in the B2B and technology sectors, to move beyond traditional SEO practices that often rely on guesswork. Instead, Fanatis advocates for a math-driven approach that leverages data to ensure that companies can achieve exponential growth in their online visibility and traffic.As the conversation unfolds, Voniatis discusses the significant shift in user behavior from traditional search engines, which typically present a list of links, to AI-driven interactions that provide summarized answers. This evolution poses a challenge for businesses, as they must adapt to a landscape where AI can solve problems directly, potentially bypassing the need for human expertise. Voniatis argues that to remain relevant, companies must prepare for a future where AI not only recommends content but also understands the nuances of their offerings.The discussion also highlights the importance of creating unique, data-rich content that stands out in an increasingly crowded digital space. Voniatis explains that simply producing high-quality content is no longer sufficient; businesses must ensure their content correlates with AI's understanding of truth and relevance. By focusing on proprietary insights and addressing the specific needs of target audiences, companies can differentiate themselves from competitors who rely on generic SEO strategies.Finally, Voniatis outlines key metrics for measuring success in this new SEO paradigm. He emphasizes the importance of tracking both traffic sources and brand searches to gauge the effectiveness of SEO efforts. By blending data science with creative content strategies, businesses can not only improve their search rankings but also enhance their overall brand visibility and engagement in the digital marketplace. All our Sponsors: https://businessof.tech/sponsors/ Do you want the show on your podcast app or the written versions of the stories? Subscribe to the Business of Tech: https://www.businessof.tech/subscribe/Looking for a link from the stories? The entire script of the show, with links to articles, are posted in each story on https://www.businessof.tech/ Support the show on Patreon: https://patreon.com/mspradio/ Want to be a guest on Business of Tech: Daily 10-Minute IT Services Insights? Send Dave Sobel a message on PodMatch, here: https://www.podmatch.com/hostdetailpreview/businessoftech Want our stuff? Cool Merch? Wear “Why Do We Care?” - Visit https://mspradio.myspreadshop.com Follow us on:LinkedIn: https://www.linkedin.com/company/28908079/YouTube: https://youtube.com/mspradio/Facebook: https://www.facebook.com/mspradionews/Instagram: https://www.instagram.com/mspradio/TikTok: https://www.tiktok.com/@businessoftechBluesky: https://bsky.app/profile/businessof.tech
Emily Riederer is a Data Science Senior Manager at Credit Risk Modeling Capital One. Her website can be found here: https://www.emilyriederer.com/ Follow along on Bluesky: Emily: @emilyriederer.bsky.social Ellie: @epiellie.bsky.social Lucy: @lucystats.bsky.social
Talk Python To Me - Python conversations for passionate developers
If you're doing data science and have mostly spent your time doing exploratory or just local development, this could be the episode for you. We are joined by Catherine Nelson to discuss techniques and tools to move your data science game from local notebooks to full-on production workflows. Episode sponsors Agntcy Sentry Error Monitoring, Code TALKPYTHON Talk Python Courses Links from the show New Course: LLM Building Blocks for Python: training.talkpython.fm Catherine Nelson LinkedIn Profile: linkedin.com Catherine Nelson Bluesky Profile: bsky.app Enter to win the book: forms.google.com Going From Notebooks to Scalable Systems - PyCon US 2025: us.pycon.org Going From Notebooks to Scalable Systems - Catherine Nelson – YouTube: youtube.com From Notebooks to Scalable Systems Code Repository: github.com Building Machine Learning Pipelines Book: oreilly.com Software Engineering for Data Scientists Book: oreilly.com Jupytext - Jupyter Notebooks as Markdown Documents: github.com Jupyter nbconvert - Notebook Conversion Tool: github.com Awesome MLOps - Curated List: github.com Watch this episode on YouTube: youtube.com Episode #511 deep-dive: talkpython.fm/511 Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy
Can you clearly articulate what makes your data science work valuable - both to yourself and to your key stakeholders? Without this clarity, you'll struggle to stay focused and convince others of your worth.In this Value Boost episode, Dr. Peter Prevos joins Dr. Genevieve Hayes to share how creating a compelling value proposition transformed his data team from report writers to strategic partners by providing both external credibility and internal direction.This episode reveals:Why a clear purpose statement serves as both an external marketing tool and an internal compass for daily decision-making [02:09]A framework for identifying your stakeholders' true pain points and how your data skills can address them [04:48]A practical first step to develop your own value statement that aligns with organizational strategy while focusing your daily work [06:53]Guest BioDr Peter Prevos is a water engineer and manages the data science function at a water utility in regional Victoria. He runs leading courses in data science for water professionals, holds an MBA and a PhD in business, and is the author of numerous books about data science and magic.LinksConnect with Peter on LinkedInA Brief Guide to Providing Insights as a Service (IaaS)Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE
Topics covered in this episode: * The Python Language Summit 2025* Fixing Python Properties * complexipy* * juvio* Extras Joke Watch on YouTube About the show Sponsored by Posit: pythonbytes.fm/connect Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: The Python Language Summit 2025 Write up by Seth Michael Larson How can we make breaking changes less painful?: talk by Itamar Oren An Uncontentious Talk about Contention: talk by Mark Shannon State of Free-Threaded Python: talk by Matt Page Fearless Concurrency: talk by Matthew Parkinson, Tobias Wrigstad, and Fridtjof Stoldt Challenges of the Steering Council: talk by Eric Snow Updates from the Python Docs Editorial Board: talk by Mariatta PEP 772 - Packaging Governance Process: talk by Barry Warsaw and Pradyun Gedam Python on Mobile - Next Steps: talk by Russell Keith-Magee What do Python core developers want from Rust?: talk by David Hewitt Upstreaming the Pyodide JS FFI: talk by Hood Chatham Lightning Talks: talks by Martin DeMello, Mark Shannon, Noah Kim, Gregory Smith, Guido van Rossum, Pablo Galindo Salgado, and Lysandros Nikolaou Brian #2: Fixing Python Properties Will McGugan “Python properties work well with type checkers such Mypy and friends. … The type of your property is taken from the getter only. Even if your setter accepts different types, the type checker will complain on assignment.” Will describes a way to get around this and make type checkers happy. He replaces @property with a descriptor. It's a cool technique. I also like the way Will is allowing different ways to use a property such that it's more convenient for the user. This is a cool deverloper usability trick. Brian #3: complexipy Calculates the cognitive complexity of Python files, written in Rust. Based on the cognitive complexity measurement described in a white paper by Sonar Cognitive complexity builds on the idea of cyclomatic complexity. Cyclomatic complexity was intended to measure the “testability and maintainability” of the control flow of a module. Sonar argues that it's fine for testability, but doesn't do well with measuring the “maintainability” part. So they came up with a new measure. Cognitive complexity is intended to reflects the relative difficulty of understanding, and therefore of maintaining methods, classes, and applications. complexipy essentially does that, but also has a really nice color output. Note: at the very least, you should be using “cyclomatic complexity” try with ruff check --select C901 But also try complexipy. Great for understanding which functions might be ripe for refactoring, adding more documentation, surrounding with more tests, etc. Michael #4: juvio uv kernel for Jupyter ⚙️ Automatic Environment Setup: When the notebook is opened, Juvio installs the dependencies automatically in an ephemeral virtual environment (using uv), ensuring that the notebook runs with the correct versions of the packages and Python
Remora, founded in 2020 in Michigan, retrofits diesel locomotives and semi-trucks with onboard systems that capture, liquify, and purify up to 90% of CO₂ emissions – while also cutting soot, particulates, and NOₓ – then stores it for offloading and sale, sharing revenue with operators. Backed by $117 M in venture funding and piloting with major players like Union Pacific, Norfolk Southern, Ryder, Werner, and DHL, the company overcame early design issues (like waterlogging and backpressure) and is now scaling for broader deployment.–Paul is the co-founder and CEO at Remora. In 2021, he was named to the Forbes 30 Under 30 list. He earned his bachelor's degree in Statistics and Data Science from Yale University, where his research received the Porter Prize, the highest class-wide thesis prize.–In this podcast, we talked about how they got investors excited to invest $117M, why unit economics are so important, the joy of doing hard things, why expertise is overrated, the reason why reading biographies is so helpful, how he got the idea for this company as a senior at Yale University, why you should watch the movies Tommy Boy and Braveheart, and how the cost of capital influenced his choice of business model.–
Talk Python To Me - Python conversations for passionate developers
Are you using Polars for your data science work? Maybe you've been sticking with the tried-and-true Pandas? There are many benefits to Polars directly of course. But you might not be aware of all the excellent tools and libraries that make Polars even better. Examples include Patito which combines Pydantic and Polars for data validation and polars_encryption which adds AES encryption to selected columns. We have Christopher Trudeau back on Talk Python To Me to tell us about his list of excellent libraries to power up your Polars game and we also talk a bit about his new Polars course. Episode sponsors Agntcy Sentry Error Monitoring, Code TALKPYTHON Talk Python Courses Links from the show New Theme Song (Full-Length Download and backstory): talkpython.fm/blog Polars for Power Users Course: training.talkpython.fm Awesome Polars: github.com Polars Visualization with Plotly: docs.pola.rs Dataframely: github.com Patito: github.com polars_iptools: github.com polars-fuzzy-match: github.com Nucleo Fuzzy Matcher: github.com polars-strsim: github.com polars_encryption: github.com polars-xdt: github.com polars_ols: github.com Least Mean Squares Filter in Signal Processing: www.geeksforgeeks.org polars-pairing: github.com Pairing Function: en.wikipedia.org polars_list_utils: github.com Harley Schema Helpers: tomburdge.github.io Marimo Reactive Notebooks Episode: talkpython.fm Marimo: marimo.io Ahoy Narwhals Podcast Episode Links: talkpython.fm Watch this episode on YouTube: youtube.com Episode #510 deep-dive: talkpython.fm/510 Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy
Topics covered in this episode: * Free-threaded Python no longer “experimental” as of Python 3.14* typed-ffmpeg pyleak * Optimizing Test Execution: Running live_server Tests Last with pytest* Extras Joke Watch on YouTube About the show Sponsored by PropelAuth: pythonbytes.fm/propelauth66 Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: Free-threaded Python no longer “experimental” as of Python 3.14 “PEP 779 ("Criteria for supported status for free-threaded Python") has been accepted, which means free-threaded Python is now a supported build!” - Hugo van Kemenade PEP 779 – Criteria for supported status for free-threaded Python As noted in the discussion of PEP 779, “The Steering Council (SC) approves PEP 779, with the effect of removing the “experimental” tag from the free-threaded build of Python 3.14.” We are in Phase II then. “We are confident that the project is on the right path, and we appreciate the continued dedication from everyone working to make free-threading ready for broader adoption across the Python community.” “Keep in mind that any decision to transition to Phase III, with free-threading as the default or sole build of Python is still undecided, and dependent on many factors both within CPython itself and the community. We leave that decision for the future.” How long will all this take? According to Thomas Wouters, a few years, at least: “In other words: it'll be a few years at least. It can't happen before 3.16 (because we won't have Stable ABI support until 15) and may well take longer.” Michael #2: typed-ffmpeg typed-ffmpeg offers a modern, Pythonic interface to FFmpeg, providing extensive support for complex filters with detailed typing and documentation. Inspired by ffmpeg-python, this package enhances functionality by addressing common limitations, such as lack of IDE integration and comprehensive typing, while also introducing new features like JSON serialization of filter graphs and automatic FFmpeg validation. Features : Zero Dependencies: Built purely with the Python standard library, ensuring maximum compatibility and security. User-Friendly: Simplifies the construction of filter graphs with an intuitive Pythonic interface. Comprehensive FFmpeg Filter Support: Out-of-the-box support for most FFmpeg filters, with IDE auto-completion. Integrated Documentation: In-line docstrings provide immediate reference for filter usage, reducing the need to consult external documentation. Robust Typing: Offers static and dynamic type checking, enhancing code reliability and development experience. Filter Graph Serialization: Enables saving and reloading of filter graphs in JSON format for ease of use and repeatability. Graph Visualization: Leverages graphviz for visual representation, aiding in understanding and debugging. Validation and Auto-correction: Assists in identifying and fixing errors within filter graphs. Input and Output Options Support: Provide a more comprehensive interface for input and output options, including support for additional codecs and formats. Partial Evaluation: Enhance the flexibility of filter graphs by enabling partial evaluation, allowing for modular construction and reuse. Media File Analysis: Built-in support for analyzing media files using FFmpeg's ffprobe utility, providing detailed metadata extraction with both dictionary and dataclass interfaces. Michael #3: pyleak Detect leaked asyncio tasks, threads, and event loop blocking with stack trace in Python. Inspired by goleak. Use as context managers or function dectorators When using no_task_leaks, you get detailed stack trace information showing exactly where leaked tasks are executing and where they were created. Even has great examples and a pytest plugin. Brian #4: Optimizing Test Execution: Running live_server Tests Last with pytest Tim Kamanin “When working with Django applications, it's common to have a mix of fast unit tests and slower end-to-end (E2E) tests that use pytest's live_server fixture and browser automation tools like Playwright or Selenium. ” Tim is running E2E tests last for Faster feedback from quick tests To not tie up resources early in the test suite. He did this with custom “e2e” marker Implementing a pytest_collection_modifyitems hook function to look for tests using the live_server fixture, and for them automatically add the e2e marker to those tests move those tests to the end The reason for the marker is to be able to Just run e2e tests with -m e2e Avoid running them sometimes with -m "not e2e" Cool small writeup. The technique works for any system that has some tests that are slower or resource bound based on a particular fixture or set of fixtures. Extras Brian: Is Free-Threading Our Only Option? - Interesting discussion started by Eric Snow and recommended by John Hagen Free-threaded Python on GitHub Actions - How to add FT tests to your projects, by Hugo van Kemenade Michael: New course! LLM Building Blocks in Python Talk Python Deep Dives Complete: 600K Words of Talk Python Insights .folders on Linux Write up on XDG for Python devs. They keep pulling me back - ChatGPT Pro with o3-pro Python Bytes is the #1 Python news podcast and #17 of all tech news podcasts. Python 3.13.4, 3.12.11, 3.11.13, 3.10.18 and 3.9.23 are now available Python 3.13.5 is now available! Joke: Naming is hard
Talk Python To Me - Python conversations for passionate developers
If you're looking to leverage the insane power of modern GPUs for data science and ML, you might think you'll need to use some low-level programming language such as C++. But the folks over at NVIDIA have been hard at work building Python SDKs which provide nearly native level of performance when doing Pythonic GPU programming. Bryce Adelstein Lelbach is here to tell us about programming your GPU in pure Python. Episode sponsors Posit Agntcy Talk Python Courses Links from the show Bryce Adelstein Lelbach on Twitter: @blelbach Episode Deep Dive write up: talkpython.fm/blog NVIDIA CUDA Python API: github.com Numba (JIT Compiler for Python): numba.pydata.org Applied Data Science Podcast: adspthepodcast.com NVIDIA Accelerated Computing Hub: github.com NVIDIA CUDA Python Math API Documentation: docs.nvidia.com CUDA Cooperative Groups (CCCL): nvidia.github.io Numba CUDA User Guide: nvidia.github.io CUDA Python Core API: nvidia.github.io Numba (JIT Compiler for Python): numba.pydata.org NVIDIA's First Desktop AI PC ($3,000): arstechnica.com Google Colab: colab.research.google.com Compiler Explorer (“Godbolt”): godbolt.org CuPy: github.com RAPIDS User Guide: docs.rapids.ai Watch this episode on YouTube: youtube.com Episode #509 deep-dive: talkpython.fm/509 Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy