It takes the average reader 2 hours and 13 minutes to read Mathematics of Deep Learning by Leonid Berlyand
Assuming a reading speed of 250 words per minute. Learn more
The goal of this book is to provide a mathematical perspective on some key elements of the so-called deep neural networks (DNNs). Much of the interest in deep learning has focused on the implementation of DNN-based algorithms. Our hope is that this compact textbook will offer a complementary point of view that emphasizes the underlying mathematical ideas. 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. 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 algorithm, etc. We attempt to identify for each concept the simplest setting that minimizes technicalities but still contains the key mathematics.
Mathematics of Deep Learning by Leonid Berlyand is 132 pages long, and a total of 33,264 words.
This makes it 45% the length of the average book. It also has 41% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 3 hours and 1 minute to read Mathematics of Deep Learning aloud.
Mathematics of Deep Learning is suitable for students ages 10 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
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