We discuss seminal mathematical papers (sometimes really old 😎 ) that have shaped and established the fields of machine learning and data science as we know them today. The goal of the podcast is to introduce you to the evolution of these fields from a mathematical and slightly philosophical perspective.
We will discuss the contribution of these papers, not just from pure a math aspect but also how they influenced the discourse in the field, which areas were opened up as a result, and so on.
Our podcast episodes are also available on our youtube:
https://youtu.be/wThcXx_vXjQ?si=vnMfs
Maths on the Move, the podcast from plus.maths.org, will bring you the latest news from the world of maths, plus interviews and discussions with leading mathematicians and scientists about the maths that is changing our lives. Hosted by Plus editors Rachel Thomas and Marianne Freiberger.
Hosted by Gabriel Hesch and Autumn Phaneuf, who have advanced degrees in electrical engineering and industrial engineering/operations research respectively, come together to discuss mathematics as a pure field all in its own as well as how it describes the language of science, engineering, and even creativity.
Breaking Math brings you the absolute best in interdisciplinary science discussions - bringing together experts in varying fields including artificial intelligence, neuroscience, evolutionary biology, physics, chemistry and materials-science, and more - to discuss where humanity is headed.
website: breakingmath.io
linktree: linktree.com/breakingmathmedia
email: breakingmathpodcast@gmail.com
Keep it casual with the Casual Inference podcast. Your hosts Lucy D'Agostino McGowan and Ellie Murray talk all things epidemiology, statistics, data science, causal inference, and public health. Sponsored by the American Journal of Epidemiology.
The Boston Computation Club is a small seminar group focused on mathematical computer science, and computational mathematics. Its name is plagiarized from the London Computation Club. Boston Computation Club meetings occur roughly every other week, on weekends, around 5pm EDT (modulo speaker availability). The usual format is a 20m presentation followed by 40m of discussion. Some, but not all, meetings are posted on YouTube and in podcast form.
This is a machine-learning-focused Podcast, where we interview people in the field of Artificial Intelligence and discuss interesting technical topics of Machine Learning. In the episodes, we focus on business-related use-cases (especially with Deep Learning ) and we also try to bring some technical white papers to the ground, not forgetting on the way that there are always some people behind the technology, so we try to understand their motivation and drive.
After-Math disini didefinisikan sebagai Setelah Matematika. Maksudnya akan dibahas kehidupan setelah kehidupan perkuliahan Matematika yaitu prospek pekerjaan seorang matematikawan yang saat ini so brighttt dan mulai banyak dilirik! Untuk kamu yang sedang gundah gulana bertemu epsilon delta dan ingin tau aplikasinya di dunia kerja check this out!
On closer inspection, we find science and especially mathematics throughout our everyday lives, from the tap to automatic speed regulation on motorways, in medical technology or on our mobile phone. What the researchers, graduates and academic teachers in Karlsruhe puzzle about, you experience firsthand in our podcast "The modeling approach".
A Math Podcast for Math Students is here to help you master your math degree, one topic at a time. Each episode dives into key concepts from your assignments, breaking them down into easy-to-understand, fun explanations. Whether you're revisiting what you learned in class or preparing for exams, we make it simple to stay on top of your studies and keep those important ideas fresh in your mind. Perfect for math students who want to review, learn, and succeed in a stress-free way!
The authors of the new paper *Self-Adapting Language Models (SEAL)* shared a behind-the-scenes look at their work, motivations, results, and future directions. The paper introduces a novel method for enabling large language models (LLMs) to adapt their own weights using self-generated data and training directives — “self-edits.” Learn more about the Self-Adapting Language Models paper. Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on Lin...
This podcast series that embarks on a deep dive into the world of MATLAB and its transformative power for engineers and scientists. I'm your host, Marco Roggero, and over the last 18 years, I've been both a student and a guide through the intricate labyrinths of MATLAB's capabilities, witnessing how it revolutionizes workflows across diverse disciplines.
