Название: Math and Architectures of Deep Learning (MEAP)
Автор: Krishnendu Chaudhury
Издательство: Manning Publications
Год: 2022 V10
Формат: True PDF
Страниц: 494
Размер: 49,1 Mb
Язык: English

The mathematical paradigms that underlie deep learning typically start out as hard-to-read academic papers, often leaving engineers in the dark about how their models actually function. Math and Architectures of Deep Learning bridges the gap between theory and practice, laying out the math of deep learning side by side with practical implementations in Python and PyTorch. Written by deep learning expert Krishnendu Chaudhury, you’ll peer inside the “black box” to understand how your code is working, and learn to comprehend cutting-edge research you can turn into practical applications.
About the Technology
It’s important to understand how your deep learning models work, both so that you can maintain them efficiently and explain them to other stakeholders. Learning mathematical foundations and neural network architecture can be challenging, but the payoff is big. You’ll be free from blind reliance on prepackaged DL models and able to build, customize, and re-architect for your specific needs. And when things go wrong, you’ll be glad you can quickly identify and fix problems.