🧪 Causal inference is about understanding why things happen, not just what @alex-andorra.bsky.social talks with Sam Witty about ChiRho & how probabilistic programming is reshaping interventions, counterfactuals, and the future of causal reasoning 🎧 learnbayesstats.com/episode/141-... #newepisode

🏈 NFL meets Bayesian stats! In this episode @alex-andorra.bsky.social chats with Ron Yurko on 👉 Writing your own models 👉 Building a sports analytics portfolio 👉 Pitfalls of modelling expectations 👉 Using tracking data for player insights 👉 Causal thinking in football data 🎧 lnkd.in/gWz4v2JG

What if your optimization algorithm could explain its uncertainty as clearly as its results?” 🤔 In this episode🎙️ @alex-andorra.bsky.social dives into Bayesian optimization, BoTorch, and why uncertainty matters with Maximilian Balandat 🎧 Listen here: lnkd.in/gg6fcfFU #bayesian #pytorch #podcast

Your deep learning model might be confidently wrong — and in medicine or epidemiology, that’s dangerous. In this episode, @alex-andorra.bsky.social chats with Mélodie Monod, François-Xavier & Yingzhen Li about making neural nets more reliable, Bayesian LLMs & more 🎧 lnkd.in/gcaRQXcb #bayes #llm

Models need more than pattern-matching. They need causal understanding. In this episode, Robert Ness joins @alex-andorra.bsky.social to explore: ⚡ Why models need real-world biases 🧠 How causal rep learning is reshaping AI 🤖 What it takes to add causality to DL 🎧 lnkd.in/gUnCkwEP #bayes #podcast

🚨 MCMC or INLA? 🤯 MCMC = slow sampling. ⚡ INLA = fast, smart approximations. No chains, no waiting. 🎙️ On LBS, @alex-andorra.bsky.social talks with Haavard Rue & Janet Van Niekerk about how INLA works, when to use it, and why it’s a game-changer. 🎧 Listen: lnkd.in/gp8D-RuU #Bayesian #MCMC

🚨 Tired of MCMC cooking your CPU for hours? @alex-andorra.bsky.social chats with Haavard Rue & Janet van Niekerk about INLA, a fast, deterministic game-changer for inference at scale. ✅ Handles huge + complex models ✅ Works with non-Gaussian likelihoods 🎧 www.learnbayesstats.com/episode/136-...

🧲 Got 50 predictors, but only 5 that matter? Try the Horseshoe Prior — a Bayesian approach to sparse regression that shrinks noise, not signal. Built with Bambi + @pymc.io 🔗 Full demo: bambinos.github.io/bambi/notebo... #BayesianStatistics #Regression #HorseshoePrior #MarketingAnalytics #PyMC

New episode is out! A very practical one, where we dive into *how* to make sure your models *actually* answer the questions you're asking...

🔍 Most Bayesian models aren’t properly checked Even when they converge, they might be wrong in ways you won’t see—unless you look differently In this episode, Teemu Säilynoja joins @alex-andorra.bsky.social to explore, SBC, prior predictive checks and more! 🎧 learnbayesstats.com/episode/135-...

Your model says 97% confidence But should you trust it? Uncertainty in ML is still a hard problem We’re hosting a meetup at Imperial College London on June 24 to dig into it — with our host @alex-andorra.bsky.social and other researchers working on better ways forward 🔗 lnkd.in/eainEJ9p

New episode is out! In this one we nerd out quite deep on zero-sum constraints, and how to make your model sample faster 💨

Some people think R² doesn’t belong in Bayesian models 👇 David Kohns disagrees, and he has the math to back it 🎙️Ep. 134: @alex-andorra.bsky.social sits down with economist David Kohns to explore how modern Bayesian methods are reshaping time series modelling 🎧 learnbayesstats.com/episode/134-...

Ask me any questions you may have about this! #stats

🎙️ Ep. 133 is out now! @alex-andorra.bsky.social chats with ‪ @spinkney.bsky.social & Adrian Seyboldt about making Bayesian models more efficient without losing rigor — zero-sum constraints, Cholesky tricks, practical wins & more 🎧 learnbayesstats.com/episode/133-... #Bayesianstats #podcast #LBS

🎙️ In episode #132 of LBS, @alex-andorra.bsky.social talks with Tom Griffiths about Bayesian cognition and human-AI interaction—how we learn from limited data, why priors matter, what AI gets wrong, and why solving real problems beats perfect models & more ... 🔗 learnbayesstats.com/episode/132-...

⚽️ New Learning Bayesian Stats ep! @alex-andorra.bsky.social & Luke Bornn dive into how tracking data, probabilistic models & optimization are reshaping sports decisions. 🎧 Listen now: learnbayesstats.com/episode/131-... #Datascience #Optimization #SportsAnalytics #BayesStats #Decisionmaking

🚨 LIVE SHOW ALERT 🚨 If you're a Patron, join us tomorrow April 24, 11:00am, US Eastern Time, with David Kohns, co-author of "The ARR2 Prior: Flexible Predictive Prior Definition for Bayesian Auto-Regressions" 🥳 👉 Patreon: www.patreon.com/c/learnbayes... 👉 YouTube: www.youtube.com/@learningbay...

Enjoyed this wide ranging discussion of how we use data and models in epidemic response:

“I think of Bayesian Deep Learning as Bayesian inference in the function space” This 55 minute interview is a really good primer of the current research questions in this field, definitely recommend it!

🧬 What does real-world impact look like when public health’s on the line? 🎙️ In episode 130 of LBS, @alex-andorra.bsky.social chats with Adam Kucharski on modelling, crisis response & lessons from recent epidemics. 🎧 Listen in: learnbayesstats.com/episode/130-...

With his research on Bayesian Deep Learning, Vincent has his finger on the pulse of the time in modern AI 🤖 I’m already looking forward to tune in to this conversation between @alex-andorra.bsky.social and @vincefort.bsky.social. … and it also comes with a video version! 👇 youtu.be/3hYYGiucS0U

This was a really fun chat with @alex-andorra.bsky.social, thanks for having me on the podcast! 🙂

What if AI could know when it doesn’t know? 🎙️ @alex-andorra.bsky.social talks with @vincefort.bsky.social about Bayesian deep learning, why it matters for uncertainty, calibration & more 🎧 Tune in: learnbayesstats.com/episode/129-... #BayesianDeepLearning #MachineLearning #ReliableAI #AIResearch

⚽ Football is more than tactics and talent—it's driven by 𝐝𝐚𝐭𝐚. From 𝐩𝐥𝐚𝐲𝐞𝐫 𝐫𝐞𝐜𝐫𝐮𝐢𝐭𝐦𝐞𝐧𝐭 to 𝐦𝐚𝐭𝐜𝐡 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬, data science gives clubs a winning edge. 🎧 In the latest episode, @alex-andorra.bsky.social sits down with Matthew Penn to break it all down: 👉 learnbayesstats.com/episode/128-...

🌊 𝐒𝐡𝐚𝐫𝐤𝐬, 𝐏𝐲𝐭𝐡𝐨𝐧, 𝐚𝐧𝐝 𝐂𝐚𝐮𝐬𝐚𝐥 𝐈𝐧𝐟𝐞𝐫𝐞𝐧𝐜𝐞? 𝐘𝐞𝐬, 𝐲𝐨𝐮 𝐫𝐞𝐚𝐝 𝐭𝐡𝐚𝐭 𝐫𝐢𝐠𝐡𝐭! 🎧 In this episode, with Aaron MacNeil and @alex-andorra.bsky.social we dive deep (pun intended) into how advanced statistical methods play a surprising role in ocean conservation 🔗 learnbayesstats.com/episode/127-... #Ecology

⚾ @fonnesbeck.bsky.social (@pymc-labs.bsky.social, @pymc.io) will be at the Field of Play Conference giving a talk on Bayesian modelling in baseball. 😎 Our host, @alex-andorra.bsky.social , will also be attending, don’t miss this chance to connect and chat research! 🔗 www.fieldofplay.co.uk

📢 Episode 126 is Live! 🎧 Listen now 👉 learnbayesstats.com/episode/126-... 🎙️ In this episode with @alex-andorra.bsky.social , Will Dean from @pymc-labs.bsky.social explains how Bayesian methods are reshaping marketing analytics, from MMM to CLV estimation and more ....

🔮 𝐁𝐚𝐲𝐞𝐬𝐢𝐚𝐧 𝐒𝐩𝐨𝐫𝐭𝐬 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐢𝐬 𝐂𝐡𝐚𝐧𝐠𝐢𝐧𝐠 𝐭𝐡𝐞 𝐆𝐚𝐦𝐞! 🎙️ In this episode, @alex-andorra.bsky.social and @fonnesbeck.bsky.social break down how Bayesian methods are revolutionizing sports analytics and why the smartest teams are embracing them 🎧 𝐋𝐢𝐬𝐭𝐞𝐧 𝐧𝐨𝐰👉 learnbayesstats.com/episode/125-... #LBS

🥳𝐖𝐞 𝐦𝐚𝐝𝐞 𝐢𝐭 𝐭𝐨 𝐭𝐡𝐞 𝐓𝐎𝐏 15! 🏆 We’re beyond excited to share that 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐁𝐚𝐲𝐞𝐬𝐢𝐚𝐧 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬 has been recognized as one of the Top 15 Statistics Podcasts by Feedspot! 🙏 Thanks to our guests for sharing their knowledge, and of course, to all of you for tuning in, sending feedback! #LearnBayesStats

Really fantastic to host Jesse Grabowski on the show! I learned so much about #TimeSeries thanks to him. And there is still so much I don't know, so I guess you'll have to come back very soon Jesse ;)

🔴 𝐇𝐨𝐰 𝐓𝐨 𝐅𝐨𝐜𝐮𝐬 𝐎𝐧 𝐖𝐡𝐚𝐭 𝐌𝐚𝐭𝐭𝐞𝐫𝐬 𝐈𝐧 𝐓𝐢𝐦𝐞 𝐒𝐞𝐫𝐢𝐞𝐬 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭𝐢𝐧𝐠 🔗 learnbayesstats.com/episode/124-... ✅ 𝐈𝐧 𝐭𝐡𝐢𝐬 𝐄𝐩𝐢𝐬𝐨𝐝𝐞, 𝐲𝐨𝐮’𝐥𝐥 𝐥𝐞𝐚𝐫𝐧 𝐡𝐨𝐰 𝐭𝐨 𝐚𝐜𝐡𝐢𝐞𝐯𝐞 𝐭𝐡𝐚𝐭 with @pymc-devs.bsky.social @alex-andorra.bsky.social & Jesse Grabowski talk about state space models, simplifying forecasting, applications etc.

🚨 **Big News!** 🚨 The first two lessons of our Intuitive Bayes courses are now FREE! 🎉 Try them out to make sure they're the perfect fit before diving into the full experience

LBS is now offering YouTube Memberships! 👇 Here’s what this means for you: ✅ AMA & Community Access: Join private sessions & our exclusive Discord server! ✅ Insider Perks: Preview upcoming episodes & co-host an episode with @alex-andorra.bsky.social 😎 Join here 🔗 www.youtube.com/@learningbay...

💯What if Bayesian modelling could be faster, more flexible, and easier to interpret? 🎧 youtu.be/7POdNknJ1Es?... 🎙️ Episode 123 is here! @alex-andorra.bsky.social chats with @aloctavodia.bsky.social about ground breaking tools and ideas that are shaping the future of Bayesian workflows. #LBS #BART

🤖 How do you teach AI when the tools and best practices evolve faster than you can adopt them? 💫 I’m usually the one asking the questions, but in this episode of Learning Bayesian Statistics, @alex-andorra.bsky.social flipped the script and interviewed me. Thanks, Alex!

📢 Episode 122 is Live! 🎧 lnkd.in/gqHWm-Mv 🎙️ In this episode of LBS, @alex-andorra.bsky.social chats with @hugobowne.bsky.social about Learning and Teaching in the Age of AI! #LearningBayesianstatistics #AI #DataScience

🎙️ Episode #121 is live! 🎧 learnbayesstats.com/episode/121-... In this episode, @alex-andorra.bsky.social & @nathanielforde.bsky.social talk about: 📊 The flexibility of Bayesian approaches in modelling, key steps in model validation. ⚖️ Balancing model complexity, factor analysis and more...

Our @pydata.bsky.social tutorial with @fonnesbeck.bsky.social on Mastering #GaussianProcesses with @pymc-devs.bsky.social is now online 🥳 If you missed it live, come check it out! Enjoy & PyMCheers 🖖 Video: www.youtube.com/watch?v=u6I5... GitHub repo: github.com/AlexAndorra/...

📢 Episode 120 is Live! 🎧 learnbayesstats.com/episodes/8f3... 🎙️ In this LBS episode, @alex-andorra.bsky.social , Liza Semenova, and Chris Wymant explore the intersection of epidemiology, Bayesian statistics, and data science! #LearningBayesianStatistics #Epidemiology #Bayesian