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Q&A: How mathematics can reveal the depth of deep learning AI

Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms as well as supporting myriad research applications. Of particular interest ...
I Programmer

Math for Deep Learning (No Starch Press)

This book, subtitled "What You Need to Know to Understand Neural Networks" provides the essential math to follow deep learning discussions, explore more complex implementations, and better use the ...
I Programmer

Mathematics of Deep Learning: An Introduction (De Gruyter)

This book sets out to provide a mathematical perspective on some key elements of deep neural networks (DNNs). Leonid Berlyand and Pierre-Emmanuel Jabin's compact textbook offers a view that emphasizes ...
The Brooklyn Paper

Math Reimagined: Achievement First’s Approach to Deep Learning and Student-Led Problem Solving

In recent decades, K-12 math education has evolved significantly, shifting from rote memorization to fostering conceptual understanding and problem-solving skills. Achievement First (AF), a network of ...

What is Deep Learning? Understanding it by thinking of it as 'stacking layers'

Hear terms like "deep learning" in the news or at work, but are not clear on how it differs from AI or machine learning. Want ...

Proposals for MEXT's Next Course of Study (Part 3): How to Realize 'Deep Learning' and 'Easy-to-Understand Learning'—Centering School Education on 'Visualization o…

This third installment is an important one that concretely demonstrates the uniqueness of Grand Design Education.In Section 3 ...
umass

Jiequn Han: Deep Picard Iteration: Solving High-Dimensional PDEs via Regression-Based Learning

Abstract: Deep learning has opened new possibilities for solving high-dimensional partial differential equations (PDEs), a longstanding challenge due to the notorious "curse of dimensionality." Early ...