Nature

Information Bottleneck in Deep Learning and Neural Networks

The information bottleneck (IB) principle is a powerful information‐theoretic framework that seeks to compress data representations while preserving the information most pertinent to a given task.
Analytics Insight

Best Neural Networks Courses in 2026 for AI and Deep Learning

Overview Neural networks courses in 2026 focus heavily on practical deep learning frameworks such as TensorFlow, PyTorch, and ...
Gizmodo

Machine Learning vs. Deep Learning: What’s the Difference?

Artificial intelligence is everywhere these days, but the fundamentals of how this influential new technology work can be difficult to wrap your head around. Two of the most important fields in AI ...
Booth School of Business

Paper Deep Neural Networks for Estimation and Inference

We study deep neural networks and their use in semiparametric inference. We establish novel rates of convergence for deep feedforward neural nets. Our new rates are sufficiently fast (in some cases ...
Ars Technica

How a stubborn computer scientist accidentally launched the deep learning boom

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...

IIT Kanpur Offers New AI and Machine Learning Certification Programs

IIT Kanpur has introduced new specialized 4-week courses in Artificial Intelligence and Machine Learning. Check details for ...
eWeek

Deep Learning vs Generative AI: Understanding the Key Differences

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...