Learning Bayesian Statistics’ Post

Very informative and non-technical. I urge everyone to watch this podcast. #mathematics #machinelearning #AI #deeplearning https://lnkd.in/g77KzhzC

scikit-learn is more important than ever, even (and especially) in the age of GenAI! We talk about that with the guys from :probabl. on the latest Practical AI Podcast! #ai #datascience #podcast

🙏 Thank you Daniel Whitenack and Chris Benson for hosting Guillaume Lemaitre and me on your excellent Practical AI Podcast 🎙️📡 ✨ Episode #296 - scikit-learn & data science you own ✨ 👉 https://lnkd.in/ehqkd8ha 📓 Chapters: - Welcome to Practical AI Podcast - What is :probabl.? - Stewarding #OpenSource projects - What is scikit-learn? - The #DataScience landscape - Scikit’s role with general purpose models - Further development - :probabl.'s open source relationship - Fun & interesting use-cases - Getting started for new devs - Future of scikit-learn & :probabl. - Outro

🎧Tune in to the latest episode of the #ImprovingAlpha #podcast, powered by Vidrio Financial and supported by Alternatives Watch, The Fund Marketer, and PEVCTech This episode features Chris Wiggins, Chief Data Scientist at The The New York Times and Associate Professor of Applied Mathematics at Columbia Business School. Join the conversation as Chris explores whether allocators have gained sufficient scar tissue by leveraging #artificialintelligence 🤖. https://hubs.li/Q02FzzX70

I am personally a visual learner and prefer to consume information through images and reading. That said, my journey to podcasts was a long one, and I remain very selective about the shows I choose. Here are my top three podcasts that boost my productivity during commute time: 1. Recsperts (https://lnkd.in/d5VuMjvg) - Every episode is a crafted gem! 2. Latent Space (https://lnkd.in/dA6bM6mj) - My go-to podcast for keeping up with the fast-moving world of AI news. 3. Vanishing Gradients (https://lnkd.in/dPeTDZue) - A recent discovery of mine, featuring great conversations with top industry experts.

Did you know that the logistic regression formulation using the logit linearization method and maximum likelihood derivation were introduced by a Medical Doctor? The paper: "Application of the logistic function to bio-assay" (1944), by Dr. Berkson Joseph is the topic of our new Data science decoded podcast. I am attaching one of our tutorials on the subject as a PDF document. Feel free to go to our website and read other tutorials and listen to the podcast. https://lnkd.in/gD7ay8Ya #datascience #machinelearning #ai #statistics #logisticregression

Excited to share my latest professional achievement. The best part was the group of people I got to connect with, from various countries, various stages in their career..all brilliant and masters in their craft! I have a new community I get the privilege of being part of. The group (Infoscience) hosts a fun Think Tank every weekend. Try it.. best way to learn what’s new in a podcast style easy chat with the experts in the field. AI Think Tank Podcast

Enhance Your Intro to Data Science or Statistics Course with AI-powered Podcasts! If you're teaching an introductory course in data science or statistics, here's a resource you might find helpful for your students. Using Google NotebookLM, I created an 8-episode podcast series designed to align with a typical semester schedule. The episodes cover essential topics, beginning with discrete and continuous distributions, advancing through sampling distributions and the Central Limit Theorem, and concluding with Linear Regression. While tailored for graduate-level students, the content is accessible and engaging enough for anyone with an interest in data—even those without a technical background. Each episode is concise, running between 10 to 17 minutes, and offers solid topic coverage without overwhelming technical jargon. I ask my students to listen before class, and the feedback has been overwhelmingly positive! How you can use it: Assign episodes as pre-class preparation. Craft in-class discussion questions or activities based on the episodes to encourage engagement. This approach has helped me create a more interactive and prepared classroom environment. https://lnkd.in/gD9Xub4s #TeachingTips #DataScience #Statistics #EdTech #GraduateEducation #PodcastsInLearning

If you’re looking to get up to speed on the latest in #GraphRAG patterns and how to navigate #GenAI & GraphRAG conversations, this 45-min conversation between Ben Lorica 罗瑞卡 from the The Data Exchange Podcast and Neo4j's CTO Philip Rathle packs in a lot of the latest points of view & learnings. Philip also shares real-world examples of companies using GraphRAG in production for applications like #enterprisesearch, #supplychain #riskanalysis, and #criminalinvestigations. You’ll also find some bonus talking points around #GQL (Graph Query Language), recently acknowledged by ISO - International Organization for Standardization. Find the #Neo4j Graph builder in the first comment of this post and start playing around with it. :) #neo4j #dataexchange #podcast #graphrag #GQL https://lnkd.in/et7pkxmd

Dr. Luca Antiga joins host Jon Krohn to discuss PyTorch Lightning's impact on AI development, the rise of small language models, and the evolving role of developers in an AI-powered world. Watch the full episode here: https://bit.ly/sds831 Thank you to Keith McCormick and Open Data Science Conference (ODSC) for supporting this episode of SuperDataScience, enabling the show to be freely available on all major podcasting platforms and on YouTube. #datascience #pytorchlightning #slms