Understanding Neural Networks

In this episode, Kyle Polich sits down with Cory Zechmann, a content curator working in streaming television with 16 years of experience running the music blog "Silence Nogood." They explore the intersection of human curation and machine learning in content discovery, discussing ... Show More

In this episode, Santiago de Leon takes us deep into the world of eye tracking and its revolutionary applications in recommender systems. As a researcher at the Kempelin Institute and Brno University, Santiago explains the mechanics of eye tracking technology—how it captures gaze ... Show More

In this episode of Data Skeptic, we dive deep into the technical foundations of building modern recommender systems. Unlike traditional machine learning classification problems where you can simply apply XGBoost to tabular data, recommender systems require sophisticated hybrid ap ... Show More

Today we’re joined by Sophia Sanborn, a postdoctoral scholar at the University of California, Santa Barbara. In our conversation with Sophia, we explore the concept of universality between neural representations and deep neural networks, and how these principles of efficiency pro ... Show More

<p>In this episode, I explore the cutting-edge technology of graph neural networks (GNNs) and how they are revolutionizing the field of artificial intelligence. I break down the complex concepts behind GNNs and explain how they work by modeling the relationships between data poin ... Show More

<p>In this episode, we talk with Jeff Hawkins—an entrepreneur and scientist, known for inventing some of the earliest handheld computers, the Palm and the Treo, who then turned his career to neuroscience and founded the Redwood Center for Theoretical Neuroscience in 2002 and Nume ... Show More

<p>Andy Kitchen is a consultant and researcher in machine learning specializing in neural networks. He sits down with Scott and explains why Machine Learning matters, and why you and I should start learning it ourselves, right away, with TensorFlow!</p> 

<p>What does it mean to solve a problem in our universe? That's a trickier question than you might think, with some fairly high-stakes ramifications in the worlds of computing and even philosophy. In this episode of Stuff to Blow Your Mind, Robert and Joe explore the inherent log ... Show More

Le deep learning ou l’apprentissage profond est un type d'intelligence artificielle dérivé du machine learning qui signifie lui apprentissage automatique. Ici, la machine est capable d'apprendre par elle-même, contrairement à la programmation où elle se contente d'exécuter à la l ... Show More

<p dir="ltr">Welcome to episode #126 of Eye on AI with Craig Smith and Noam Chomsky.<br /> <br /> Are neural nets the key to understanding the human brain and language acquisition? In this conversation with renowned linguist and cognitive scientist <a href= "https://twitter.com/c ... Show More

The intersection between cutting-edge neuroscience and the emerging field of network science has been growing tremendously over the past decade. Olaf Sporns, editor of Network Neuroscience, and Distinguished Professor, Provost Professor of Department of Psychological and Brain Sc ... Show More

<p>In this episode of our podcast, we dive deep into the fascinating world of Graph Neural Networks.</p> <p>First, we explore Hierarchical Networks, which allow for the efficient representation and analysis of complex graph structures by breaking them down into smaller, more mana ... Show More