MLG 008 Math

Google Veo leads the generative video market with superior 4K photorealism and integrated audio, an advantage derived from its YouTube training data. OpenAI Sora is the top tool for narrative storytelling, while Kuaishou Kling excels at animating static images with realistic, hig ... Show More

The AI image market has split: Midjourney creates the highest quality artistic images but fails at text and precision. For business use, OpenAI's GPT-4o offers the best conversational control, while Adobe Firefly provides the strongest commercial safety from its exclusively licen ... Show More

Auto encoders are neural networks that compress data into a smaller "code," enabling dimensionality reduction, data cleaning, and lossy compression by reconstructing original inputs from this code. Advanced auto encoder types, such as denoising, sparse, and variational auto encod ... Show More

In this episode I make a non exhaustive list of machine learning tools and frameworks, written in Rust. Not all of them are mature enough for production environments. I believe that community effort can change this very quickly. To make a comparison with the Python ecosystem I wi ... Show More

It seems like every day there's more and more machine learning problems that involve learning on text data, but text itself makes for fairly lousy inputs to machine learning algorithms.  That's why there are text vectorization algorithms, which re-format text data so it's ready f ... Show More

🎙️ Ta minute mathématique, ton nouveau rendez-vous de l'été. Une minute pour une notion simple de mathématique abordées sous forme de question que tu as toujours voulu poser sans jamais oser le demander.Rendez-vous tous les mercredis pendant l'été.Aujourd'hui : les statistiques, ... Show More

Today I am with David Kopec, author of Classic Computer Science Problems in Python, published by Manning Publications. His book deepens your knowledge of problem solving techniques from the realm of computer science by challenging you with interesting and realistic scenarios, exe ... Show More

Vladimir Vapnik is the co-inventor of support vector machines, support vector clustering, VC theory, and many foundational ideas in statistical learning. His work has been cited over 170,000 times. He has some very interesting ideas about artificial intelligence and the nature of ... Show More

Catherine Nelson, author of the new O’Reilly book, Software Engineering for Data Scientists, discusses the collaboration between data scientists and software engineers -- an increasingly common pairing on machine learning and AI projects. Host Philip Winston speaks with Nelson ab ... Show More

Summary Biology has been gaining a lot of attention in recent years, even before the pandemic. As an outgrowth of that popularity, a new field has grown up that pairs statistics and compuational analysis with scientific research, namely bioinformatics. This brings with it a uniqu ... Show More

When math is based on abstract concepts, how do we know it’s correct? Dr. Eugenia Cheng takes on that question in a new book. The concept of math has been around for a long time, developing independently in many different cultures. In 1650 BC, the Egyptians were creating math tex ... Show More

When we think about machine learning today we often think in terms of immense scale — large language models that require huge amounts of computational power, for example. But one of the most interesting innovations in machine learning right now is actually happening on a really s ... Show More