Reading Diary #1642: 'Mathematics of Deep Learning via the Shortest Course, Expanded and Revised Edition'

Reading Notes The principle behind the learning process of machine learning and deep learning is to find parameters that ...
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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

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 ...
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 ...
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 ...
umass

Konstantinos Spiliopoulos: Normalization effects on deep neural networks and deep learning for scientific problems

We study the effect of normalization on the layers of deep neural networks. A given layer $i$ with $N_{i}$ hidden units is normalized by $1/N_{i}^{\gamma_{i}}$ with ...

What is Deep Learning? Explaining the Differences from AI and Machine Learning

An explanation of what deep learning is, tailored for beginners. We will organize the differences between AI and machine ...