Shows
🤖🧬 Where Technology Meets Science#010 Centralized Monitoring: Risk-based Approach to Clinical Trial Processes#datascience #centralizedmonitoring #clinicaltrials #technologyinpharma #pharmatransformationIn this episode, Jennifer Krohn, Associate Director of Risk-Based Quality Management at Gilead Sciences, shares how centralized monitoring is transforming clinical trial oversight, improving data quality, participant safety, and trial efficiency. From statistical tools and open-source innovation to CRA training and AI advancements, Jenn shares what it takes to detect critical data signals earlier, ensure trial integrity, and foster cross-functional collaboration in pharma through the open-source community.Materials shared in the episode:PHUSE RBQM Working GroupRBQM Education ProjectPHUSE CM White Papers:Centralized Monitoring: Exploring the Considerations and Challenges o...2025-06-2041 min
🤖🧬 Where Technology Meets Science#009 GenAI in Clinical Reporting: Beyond the Buzz, Real Use Cases, and Future Directions#datascience #genAI #clinicaltrials #clinicalreporting #AIinpharma #GenerativeAI #Roche #AIautomation #pharmaceuticalindustry #AIchallenges #AIbot #chatbots #copilot #codingassistantIn this episode, we speak with Vincent Shen, Senior Principal Data Scientist at Roche, about the actual impact of generative AI in clinical data analysis. Vincent shares insights from his work implementing AI-powered tools, such as knowledge chatbots and coding assistants, that support clinical reporting at Roche. We discuss the evolving role of AI, the challenges of integrating it into clinical trial workflows, and the importance of rethinking the processes to ensure effective AI use.In this episode:AI will augment rather than r...2025-06-0535 min
🤖🧬 Where Technology Meets Science#4 Pharma Brief: Generative AI Advances at FDA, Pharma’s Autonomous Agents, and Open-Source Tools Spotlight#datascience #dataanalysis #technology #pharmabrief #clinicaltrials #technologyinpharma #pharma #pharmanewsPharma Brief’s fourth edition spotlights generative AI’s rapid expansion across pharma and regulatory landscapes. This issue covers the FDA’s planned rollout of generative AI tools across all centers, including the launch of Elsa to streamline reviews and inspections. We explore Anthropic’s Model Context Protocol as a new standard for context-aware AI, plus pharma’s growing use of autonomous agents in clinical operations and medical writing, with insights from BCG’s latest report.Benchling’s integration of Claude into biotech R&D workflows highlights sig...2025-06-0406 min
🤖🧬 Where Technology Meets Science#008 Machine Learning Modeling in Neuroscience Clinical Trials Design#datascience #dataanalysis #technology #machinelearning #clinicaltrials #placeboIn this episode, Jing Dai, Director of Biostatistics at Jazz Pharmaceuticals, shares insights from the PHUSE US Connect conference and her work on applying machine learning to neuroscience clinical trials. She discusses challenges like high placebo response and attrition, the value of interdisciplinary collaboration, and how AI/ML can shape trial design, improve regulatory readiness, and move the field toward more objective, data-driven outcomes.In this episode, you will learn:How machine learning can help address high placebo response and attrition in neuroscience clinical trials.Why traditional...2025-05-2234 min
🤖🧬 Where Technology Meets Science#007 How Open Source and Community Efforts Drive R-Based FDA Submissions#datascience #dataanalysis #technology #datascience #opensource #pharmaverse #pharma #dataanalysis #clinicaltrialsIn this episode, Ben Straub, Principal Programmer at GSK, explores the shift from proprietary software to open source tools in the pharmaceutical industry. He shares insights into regulatory challenges, the rise of R, and the impact of {admiral} and other open-source packages on clinical data analysis and submissions. From pilot programs to enterprise-wide adoption, learn why collaboration is key to reducing risk and shaping the future of regulatory workflows.In this episode, you will learn:Lessons learned from GSK’s open source adoption jo...2025-05-0835 min
🤖🧬 Where Technology Meets Science#3 Pharma Brief: FDA's Animal Testing Phase-Out, AI in Clinical Development, and Open-Source News#datascience #dataanalysis #technology #pharmabrief #clinicaltrials #technologyinpharma #pharma #pharmanewsPharma Brief is back with its third edition, packed with essential industry insights and the latest developments in pharma and biotech. This issue covers the FDA’s plan to phase out animal testing for monoclonal antibodies in favor of AI models and NAMs, insights from Stanford’s AI Index 2025 and McKinsey’s analysis of AI in clinical development, plus new tools like CDISC Dataset Generator, scMultiSim, open-source releases from Novo Nordisk and Genentech and more! You can follow Pharma Brief on LinkedIn: https://www.linkedin.com/newsletters/pharma-brief-7300489155535380480/A...2025-05-0706 min
🤖🧬 Where Technology Meets Science#006 Inside Novo Nordisk’s Path to Open Source for the Pharma and BeyondAri Siggaard Knoph from Novo Nordisk shares how the company transitioned from SAS to R for FDA submissions. From early Shiny apps to full-scale open-source workflows, learn how this shift accelerated innovation, attracted top talent, and redefined clinical programming. In this episode, you will learn:How Novo Nordisk transitioned from legacy systems to R for regulatory submissionsHow Shiny applications became the catalyst for internal buy-inHow open-source adoption has broadened the company’s talent pool and improved productivityFuture directions in pharma tech__________________________________________More about Appsilon:► https://www.appsilon.com/Appsilon empowers pharmaceutical and life sciences companies to le...2025-04-2432 min
🤖🧬 Where Technology Meets Science#005 Shiny’s Evolution: From Prototyping Tool to Critical Technology in Pharma#datascience #dataanalysis #technology #clinicaltrials #rshiny #shinyforpython #pharmatechShiny paved the way for R users to create interactive, production-ready applications without switching stacks. In this episode, Eric Nantz reflects on Shiny’s origins, its "lazy by design" reactivity model, and how the ecosystem matured. We dive into how Shiny for Python expands this power to new audiences, and how Shiny is becoming key to modern clinical trial workflows. Eric shares real-world examples, user reactions, and the future of interactive data science.In this episode, you will learn:Ho...2025-04-1035 min
🤖🧬 Where Technology Meets Science#2 Pharma Brief: AI’s Impact on Clinical Trials, Must-See Open Source Tools, and Upcoming Pharma EventsPharma Brief is back with the latest edition, packed with valuable insights and upcoming events you don’t want to miss. This month, we’re exploring AI’s impact on clinical development (trials could be 30% faster!), along with innovative tools that streamline processes. We’ve also highlighted open-source packages to optimize your workflows.You can follow Pharma Brief on LinkedIn: https://www.linkedin.com/newsletters/pharma-brief-7300489155535380480/ And now it’s available in audio on all your favorite podcasting platforms.Links from the episode:NVIDIA’s “State of AI in Healthcare and Life Sciences” Report: https://blogs.nvidia.com/blog...2025-04-0205 min
🤖🧬 Where Technology Meets Science#004 Technology Transformation in Clinical Trial Analysis#datascience #dataanalysis #technology #clinicaltrials #opensource #rshiny #techtransformationThe opinions shared here do not represent the official position of Roche or Novartis.We explore why clinical trials lag behind in innovation—even as the research side of drug development makes massive leaps. We’ll uncover why attracting top talent is critical to driving the industry forward, particularly in adopting open-source technologies. Dive into tools like R, test automation frameworks, and data abstractions, and learn how they’re reshaping tech transformation in clinical trials. Joining us are Novartis experts Orla Doyle and James Black to unpack the challenges and op...2025-03-2740 min
🤖🧬 Where Technology Meets Science#1 Pharma Brief: J&J Moves to Open Source, AI-powered Data Extraction, and Top Clinical Trials for 2025Pharma Brief delivers your monthly pulse on pharma’s evolving landscape. Stay ahead with curated insights on FDA/EMA updates, AI-driven trends, and must-attend global events. We unpack breakthroughs—from novel drug approvals to open-source tools like R/Shiny—and arm you with actionable resources to in tech transformations in clinical trials. Whether it’s GxP compliance strategies or clinico-genomic advancements, we’re here to sharpen your expertise.You can follow it on LinkedIn: https://www.linkedin.com/newsletters/pharma-brief-7300489155535380480/ and now it’s available in the audio on all your favorite podcasting platforms.Links from t...2025-03-2005 min
🤖🧬 Where Technology Meets Science#003 The Future of GxP Compliance in Pharma: R-based Submissions#datascience #dataanalysis #GxP #PharmaTech #SoftwareValidation #FDARegulations #ClinicalTrials #LifeSciences #R #PharmaInnovation #TechInPharmaGxP compliance is shaping the future of pharmaceutical software engineering, yet many companies still struggle with implementation. In this episode, Appsilon’s co-founder, Paweł Przytuła, unpacks GxP best practices, software validation, and how R-based submissions are gaining traction with regulatory bodies like the FDA. He also shares industry insights from Roche, Novo Nordisk, and GSK, explores emerging trends like AI in validation, and discusses how pharma companies can leverage open-source tools while ensuring compliance. Don’t miss this deep dive into the intersection of software and life scienc...2025-03-1334 min
🤖🧬 Where Technology Meets Science#002 How NASA Chooses the Right Talent for Space ExplorationIn this episode of Technology Meets Science, we welcome David Meza, Head of Analytics at NASA’s Human Capital Office. David shares how data science and AI are transforming talent management at NASA, ensuring the right individuals are matched with critical missions. From knowledge graphs to generative AI, he explains how NASA is leveraging technology to optimize workforce planning, upskilling, and recruitment. Tune in for insights on AI-driven talent analytics, the challenges of data accessibility, and what it takes to land a career at NASA.In this episode, you will learn:How NASA uses data sc...2025-02-2727 min
🤖🧬 Where Technology Meets Science#001 Why Clinical Trials Fail: Lessons from Two Decades in PharmaTogether with Eric Genevois-Marlin, former Head of Data Sciences in R&D and Biostatistics at Sanofi, we uncover the reasons behind clinical trial failures. Drawing from his 20+ years of experience leading science and technology teams in bringing new drugs to market, we'll examine real-world examples and extract lessons from both successes and failures.In this episode, you will learn:What the risks are in clinical trialsThe main causes of clinical trial failuresExamples of success storiesLessons learned from clinical trials that go wrongHow to minimize the risks of failure__________________________________________More about Appsilon:► https://www.appsilon.com/Ap...2025-02-1333 min
🤖🧬 Where Technology Meets Science#000 Where Technology Meets Science by Appsilon Trailer"Where Technology Meets Science" is a podcast series diving into the intersection of technology and life sciences. We bring together industry experts, innovators, and thought leaders to explore how advanced technologies are reshaping data science processes in biotechnology, biopharma, environmental sciences, genetics, and similar fields. Together with experts from companies like Roche, Novartis, NASA, and J&J, we uncover solutions that address complex challenges, accelerate research, and push beyond traditional scientific methods, offering listeners insights into the evolving landscape of scientific discovery.2025-02-0701 min
Porozmawiajmy o ITCzy sztuczna inteligencja zmieni rynek pracy w IT? Gość: Julia Szopa - POIT 270Witam w dwieście siedemdziesiątym odcinku podcastu „Porozmawiajmy o IT”. Tematem dzisiejszej rozmowy jest to czy sztuczna inteligencja zmieni rynek pracy w IT.Dziś moim gościem jest Julia Krysztofiak-Szopa – uczy firmy, jak działać efektywniej dzięki Sztucznej Inteligencji i Chat GPT. Doświadczona specjalistka w dziedzinie innowacji biznesowych i Sztucznej Inteligencji, łączy pasję do technologii z praktycznym zrozumieniem jej wpływu na biznes i społeczeństwo. Z branżą nowych technologii związana od 2008 roku. Była prezeską Startup Poland, dyrektorką programową w Blackbox VC i COO w Appsilon. Jest także autorką podcastu “Dzi...2025-01-0846 min
Porozmawiajmy o ITCzy sztuczna inteligencja zmieni rynek pracy w IT? Gość: Julia Szopa - POIT 270Witam w dwieście siedemdziesiątym odcinku podcastu „Porozmawiajmy o IT”. Tematem dzisiejszej rozmowy jest to czy sztuczna inteligencja zmieni rynek pracy w IT.Dziś moim gościem jest Julia Krysztofiak-Szopa – uczy firmy, jak działać efektywniej dzięki Sztucznej Inteligencji i Chat GPT. Doświadczona specjalistka w dziedzinie innowacji biznesowych i Sztucznej Inteligencji, łączy pasję do technologii z praktycznym zrozumieniem jej wpływu na biznes i społeczeństwo. Z branżą nowych technologii związana od 2008 roku. Była prezeską Startup Poland, dyrektorką programową w Blackbox VC i COO w Appsilon. Jest także autorką podcastu “Dzieci Z...2025-01-0846 min
R Weekly HighlightsIssue 2024-W49 HighlightsAs the holiday season enters the picture, learn how a humble R package helps you to give thanks to the contributors of your open-source package. Plus a practical introduction to missing value interpolation with a tried-and-true R package with a rich history, and a comprehensive analysis to predict an NBA superstar's next shot result (who has made a lot of shots already in his career).Episode LinksThis week's curator: Jon Carroll - @jonocarroll@fosstodon.org (Mastodon) & @carroll_jono (X/Twitter)Give Thanks with the allcontributors PackageHow to Interpolate Missing Values in R: A Step-by-Sthttps://github.com/ropensci...2024-12-0443 minR Weekly HighlightsIssue 2024-W30 HighlightsCreating retro-gaming sprites rendered from the comforts of R? Yes we can! Plus an honest take on the utility of Github's Copilot Workspace in the context of package development, and taking the concept of code trees to another level with treesitter.Episode LinksThis week's curator: Ryo Nakagawara - @RbyRyo@mstdn.social (Mastodon) & @RbyRyo) (X/Twitter)Tile-style sprite delightSome thoughts after a trial run of GitHub's Copilot WorkspaceExtracting names of functions defined in a script with treesitterEntire issue available at rweekly.org/2024-W30Supplement Resourcestree-sitter-r https://github.com/r-lib/tree-sitter-rShiny.telemetry 0.3.0 https://www.appsilon.com/post...2024-07-2443 minR Weekly HighlightsIssue 2024-W22 HighlightsThe recent patches in R that pave the way for a future object-oriented-programming framework to accompany S3 and S4, a treasure-trove of open spatial data ready for your mapping visualization adventures, and a collection of tips for the next time you refactor your testing scripts.Episode LinksThis week's curator: Jon Carroll - @jonocarroll@fosstodon.org (Mastodon) & @carroll_jono (X/Twitter)Generalizing Support for Functional OOP in RGetting and visualizing Overture Maps buildings data in RWhat I edit when refactoring a test fileEntire issue available at rweekly.org/2024-W22Supplement ResourcesOverture Maps https://overturemaps.orgShiny Developer...2024-05-2950 minR Weekly HighlightsIssue 2024-W19 HighlightsOur take on the important conversations spurred by the recent R deserialization CVE, how simulations may save you from cracking open that probability textbook, and recapping the exciting 2024 Shiny Conference.Episode LinksThis week's curator: Colin Fay - @colinfay@fosstodon.org & [@ColinFay]](https://twitter.com/ColinFay) (X/Twitter)Everything you never wanted to know about the R vulnerability, but shouldn't be afraid to askCalculating birthday probabilities with R instead of mathHighlights from ShinyConf 2024Entire issue available at rweekly.org/2024-W19Supplement ResourcesR-bitrary Code Execution: Vulnerability in R’s Deserialization https://hiddenlayer.com/research/r-bitrary-code-execution/CVE-2024-27322 Sh...2024-05-0849 minR Weekly HighlightsIssue 2024-W16 HighlightsAnother way to hop on LLM train with the chattr package, a clever use of defensive programming to get to those warnings in your tests faster, and a major milestone for the R-Hub project.Episode LinksThis week's curator: Tony Elhabr - @tonyelhabr@skrimmage.com (Mastodon) & @TonyElHabr (X/Twitter)Chat with AI in RStudioTest warnings fasterR-hub v2Entire issue available at rweekly.org/2024-W16Supplement ResourcesR/Pharma 2023 presentation by Edgar Ruiz (GitHub Copilot in RStudio) - https://youtu.be/-Fjb8LZmTSIThe 2024 Appsilon Shiny Conference is just days away! https://www.shinyconf.com/Supporting the show...2024-04-1636 min
R-bloggersHow to Make Your Shiny App Beautiful
[This article was first published on Tag: r - Appsilon | Enterprise R Shiny Dashboards, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Shiny apps are very often used for quick prototyping and proof of concept.
However, if you want to use a Shiny app in production and make it attractive to the users, you need to make sure that the app is not only functional but also visually appealing and...2024-02-0100 minR Weekly HighlightsIssue 2024-W03 HighlightsA tour of how the httr2 package streamlines API processing in R, five must-have ggplot2 extension packages for your next visualization, and the Appsilon Shiny Conf 2024 is shaping up to be the biggest yet for all things Shiny.
Episode Links
This week's curator: Colin Fay - [@_ColinFay]](https://twitter.com/_ColinFay) (Twitter)
How to work with APIs using the httr2 package
Five Powerful ggplot Extensions
Call for Speakers: ShinyConf 2024 by Appsilon
Entire issue available at rweekly.org/2024-W03
Supplement Resources
Eric's podindexr package (accessing the Podcast Index API from R) https://github.com/rpodcast...2024-01-1744 minR Weekly HighlightsIssue 2023-W48 HighlightsA glimpse of refactoring functional R code to object-oriented programming with R6, using benchmarking as another input to adopting package dependencies, and building a high-performance CSV reader by combining R and Rust.
Episode Links
This week's curator: Tony Elhabr - @TonyElHabr (Twitter) & @tonyelhabr@skrimmage.com (Mastodon)
Object-Oriented Express: Refactoring in R
Using benchmarking to guide the adoption of dependencies in R packages
Building a DataFusion CSV reader with arrow-extendr
Entire issue available at rweekly.org/2023-W48
Supplement Resources
Sharing app state between Shiny modules https://docs.google.com/presentation/d/13___ZiOO1aEv0xiCj2TAm2...2023-11-3050 min
Science Research WeeklyEpisode 35: Wi-Fi Reading and MicroflyingGet ready for atmospheric water harvesting, entering the lipidome, Wi-Fi reading through walls, electric-producing bacteria, shape-shifting microflyer origami robots, the return of the Journal of Statistical Software, top picks for posit::conf 2023, the TidyTuesday GitHub repository, and a grant to establish a Center for Exposome Research Coordination. Science On.
References:
Molecularly confined hydration in thermoresponsive hydrogels for efficient atmospheric water harvesting
Dynamic lipidome alterations associated with human health, disease and ageing
Analysis of Keller Cones for RF Imaging
Video of RF Imaging
An interfacial solar evaporation enabled autonomous double-layered vertical floating solar sea...2023-09-1511 minR Weekly HighlightsIssue 2023-W26 HighlightsReleasing an Word document table into the land of markdown, a practical overview of sharing your machine learning model with others, and taking local control of checking the builds of your package across computing architectures.
Episode Links
This week's curator: Colin Fay - [@_ColinFay]](https://twitter.com/_ColinFay) (Twitter)
Convert a Word table to Markdown
How Can Someone Else Use My Model?
How to debug your package in a {rhub} fedora container before sending to CRAN?
Entire issue available at rweekly.org/2023-W26
Supplement Resources
{datapasta} RStudio addins and R functions that make copy-pasting...2023-06-2833 min
EcochatAI for Conservation - Assessing Rainforest Biodiversity in Gabon, Ecosystem Health in the Arctic, and MoreHow can we apply AI to conservation? How does it even work? I invite Jędrzej Świeżewski, Head of AI at Appsilon, to learn all about AI, machine learning, neural networks, image recognition. We dive into several case studies:
Mbaza AI: A computer vision app for assessing biodiversity in Africa. It has recently been recognized by UNESCO as one of the top 10 global projects contributing to the UN's Sustainable Development Goals. https://ircai.org/top100/entry/mbaza-ai/
Monitoring the ecosystem health of the Arctic Ocean.
Counting nests...2023-05-171h 28EcochatAI for Conservation - Assessing Rainforest Biodiversity in Gabon, Ecosystem Health in the Arctic, and MoreHow can we apply AI to conservation? How does it even work? I invite Jędrzej Świeżewski, Head of AI at Appsilon, to learn all about AI, machine learning, neural networks, image recognition. We dive into several case studies:
Mbaza AI: A computer vision app for assessing biodiversity in Africa. It has recently been recognized by UNESCO as one of the top 10 global projects contributing to the UN's Sustainable Development Goals. https://ircai.org/top100/entry/mbaza-ai/
Monitoring the ecosystem health of the Arctic Ocean.
Counting nests...2023-05-171h 28R Weekly HighlightsIssue 2023-W20 HighlightsIntroducing the new ggflowchart package, how a dockerized development environment is another win for reproducibility, and our take on Colin Fay's keynote from the Appsilon Shiny Conference.
Episode Links
This week's curator: Sam Parmar - @parmsam_ (Twitter) & @parmsam@fosstodon.org (Mastodon)
Introducing {ggflowchart}
Why you should consider working on a dockerized development environment
Colin Fay, Keynote: Production is like ultra running: brutal, ungrateful, but worth every step
Entire issue available at rweekly.org/2023-W20
Supplement Resources
Episode 82 (the origins of ggflowchart) https://rweekly.fireside.fm/82
Building reproducible analytical pipelines with R https://raps-with-r.dev
...2023-05-1741 minR Weekly HighlightsIssue 2023-W15 HighlightsA data-driven look at package loading annotations in R scripts, a fit-for-purpose package that makes a large contribution to the global R ecosystem, and a collection of amazing showcases of webR in action that is paving the way for continued innovation.
Episode Links
This week's curator: Tony Elhabr - @TonyElHabr (Twitter) & @tonyelhabr@skrimmage.com (Mastodon)
What are people commenting about their loaded packages?
Introducing rtlr - an R Package for RTL Languages
hrbrmstr's WebR Experiments Index
Entire issue available at rweekly.org/2023-W15
Supplement Resources
annotater: Annotate Package Load Calls https://github.com/luisDVA...2023-04-1247 min
Pismo do słuchaniaJak naprawić przyszłość? #31: Jak dotujemy spalanie lasów?O tym, jak dotujemy spalanie naszych lasów i o aplikacji Future Forest, która pokazuje wpływ ocieplenia klimatu na przyszły skład gatunkowy i charakter europejskich lasów, rozmawiam w 31. odcinku podcastu „Jak naprawić przyszłość?”.
Dla aktywistów las to przede wszystkim część środowiska, która wymaga ochrony. W lesie większość z nas szuka także wytchnienia i relaksu. Dla polityków obsadzających stołki w Lasach Państwowych to przede wszystkim źródło surowca oraz dochodu, ma zaspokajać potrzeby różnych grup wyborców. O największych zagrożeniach dla europejskich lasów i najbardziej skutecznych sposobach...2023-01-311h 00
Jak naprawić przyszłość?Jak dotujemy spalanie lasów?O tym, jak dotujemy spalanie naszych lasów i o aplikacji Future Forest, która pokazuje wpływ ocieplenia klimatu na przyszły skład gatunkowy i charakter europejskich lasów, rozmawiam w 31. odcinku podcastu „Jak naprawić przyszłość?”.Dla aktywistów las to przede wszystkim część środowiska, która wymaga ochrony. W lesie większość z nas szuka także wytchnienia i relaksu. Dla polityków obsadzających stołki w Lasach Państwowych to przede wszystkim źródło surowca oraz dochodu, ma zaspokajać potrzeby różnych grup wyborców. O największych zagrożeniach dla europejskich lasów i najbardziej skut...2023-01-311h 00
Porozmawiajmy o ITJęzyk programowania R. Gość: Filip Stachura - POIT 171Witam w sto siedemdziesiątym pierwszym odcinku podcastu „Porozmawiajmy o IT”. Tematem dzisiejszej rozmowy jest język programowania R.Dziś moim gościem jest Filip Stachura – CEO Appsilon, który bez inwestora osiągnął pozycję lidera w domenie R / Shiny. Pasjonat danych, dataviz, Open Source i Tech4Good. Ukończył matematykę i informatykę na Uniwersytecie Warszawskim. Wcześniej pracował w Microsoft w Los Angeles.W tym odcinku o języku R rozmawiamy w następujących kontekstach:czym jest język R i do czego służy?jak powstał?kto go obecnie rozwija?skąd bierze się popularność języka R?z jakimi językami konkuruj...2022-10-1256 min
Porozmawiajmy o ITJęzyk programowania R. Gość: Filip Stachura - POIT 171Witam w sto siedemdziesiątym pierwszym odcinku podcastu „Porozmawiajmy o IT”. Tematem dzisiejszej rozmowy jest język programowania R.Dziś moim gościem jest Filip Stachura – CEO Appsilon, który bez inwestora osiągnął pozycję lidera w domenie R / Shiny. Pasjonat danych, dataviz, Open Source i Tech4Good. Ukończył matematykę i informatykę na Uniwersytecie Warszawskim. Wcześniej pracował w Microsoft w Los Angeles.W tym odcinku o języku R rozmawiamy w następujących kontekstach:czym jest język R i do czego służy?jak powstał?kto go obecnie rozwija?skąd...2022-10-1255 min