Math and architectures of deep learning, krishnendu chaudhury, ananya h. ashok, sujay naru...

Shine a spotlight into the deep learning “black box”. This comprehensive and detailed guide reveals the mathematical and architectural concepts behind deep learning models, so you can customize, maintain, and explain them more effectively. Inside Math and Architectures of Deep Learning you will find: Math, theory, and programming principles side by side Linear algebra, vector calculus and multivariate statistics for deep learning The structure of neural networks Implementing deep learning architectures with Python and PyTorch Troubleshooting underperforming models The mathematical paradigms behind deep learning models typically begin as hard-to-read academic papers that leave engine...