Mathematics of Deep Learning Berlyand Jabin Leonid Pierre-Emmanuel
Mathematics of Deep Learning Berlyand Jabin Leonid Pierre-Emmanuel The goal of this book is to provide a mathematical perspective on some key elements of the so-called deep neural networks (DNNs).…
Specifikacia Mathematics of Deep Learning Berlyand Jabin Leonid Pierre-Emmanuel
Mathematics of Deep Learning Berlyand Jabin Leonid Pierre-Emmanuel
The goal of this book is to provide a mathematical perspective on some key elements of the so-called deep neural networks (DNNs). Our hope is that this compact textbook will offer a complementary point of view that emphasizes the underlying mathematical ideas. Much of the interest in deep learning has focused on the implementation of DNN-based algorithms.
Our goal is to introduce basic concepts from deep learning in a rigorous mathematical fashion, e.g introduce mathematical definitions of deep neural networks (DNNs), loss functions, the backpropagation We believe that a more foundational perspective will help to answer important questions that have only received empirical answers so far.The material is based on a one-semester course Introduction to Mathematics of Deep Learning" for senior undergraduate mathematics majors and first year graduate students in mathematics.
Fundamentals of Deep Learning
Learning Deep Learning
Deep Learning
Deep Learning
Mathematics for Machine Learning
Generative Deep Learning
Probabilistic Deep Learning
Grokking Deep Learning
Generative Deep Learning
TensorFlow for Deep Learning