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Carnegie Mellon University at ICLR 2025

ML @ CMU

CMU researchers are presenting 143 papers at the Thirteenth International Conference on Learning Representations (ICLR 2025), held from April 24 – 28 at the Singapore EXPO. Gordon, Fei Fang Physics of Language Models: Part 2.1,

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The Math Behind Supervised Learning: Making AI Less Mysterious

Towards AI

Last Updated on February 26, 2025 by Editorial Team Author(s): Aleti Adarsh Originally published on Towards AI. Ever Wondered How AI Learns? Have you ever looked at AI models and thought, How the heck does this thing actually learn? Lets Break It Down! This member-only story is on us. Upgrade to access all of Medium.

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Pushing the Boundaries of AI-based Lossy Compression

IBM Data Science in Practice

In this article, we introduce the 2025 CVPR EARTHVISION Data Challenge an initiative by the Horizon Europe Embed2Scale consortium to advance neural compression for Earth Observation data. A CVPR EARTHVISION Data Challenge by Embed2Scale Modern compression methods redefine the way we handle and analyze satellite imagery.

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Scikit-learn from A to Z: The Complete Guide to Mastering Machine Learning in Python

Towards AI

Last Updated on January 29, 2025 by Editorial Team Author(s): Aleti Adarsh Originally published on Towards AI. We have seen how Machine learning has revolutionized industries across the globe during the past decade, and Python has emerged as the language of choice for aspiring data scientists and seasoned professionals alike.

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Bayesian State-Space Neural Networks (BSSNN): A Novel Framework for Interpretable and Probabilistic Neural Models

Towards AI

Last Updated on January 20, 2025 by Editorial Team Author(s): Shenggang Li Originally published on Towards AI. Integrating Bayesian Theory, State-Space Dynamics, and Neural Network Structures for Enhanced Probabilistic Forecasting This member-only story is on us. Upgrade to access all of Medium.

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What Is Agentic AI? A Gateway to Building Smarter and Autonomous Agents

Data Science Dojo

You can also use supervised learning if you already have labeled data to teach the agent. If you are curious about where all this is headed, make sure to check out the Rise of Agentic AI Conference by Data Science Dojo , happening on May 27 and 28, 2025. Think of it like training your agent until it can train itself.

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Unsupervised Learning Series #1: A Beginner’s Guide to Concepts and Models That Work

Towards AI

Last Updated on April 24, 2025 by Editorial Team Author(s): SETIA BUDI SUMANDRA Originally published on Towards AI. Thats the motto of Unsupervised Learning a fascinating branch of machine learning where algorithms learn patterns from unlabeled data. No Label, No Problem. Not part of the Mediums partner program?