Math and Architectures of Deep Learning sets out the foundations of DL in a way that’s both useful and accessible to working practitioners. Each chapter explores a new fundamental DL concept or architectural pattern, explaining the underpinning mathematics and demonstrating how they work in practice with well-annotated Python code. You’ll start with a primer of basic algebra, calculus, and statistics, working your way up to state-of-the-art DL paradigms taken from the latest research. By the time you’re done, you’ll have a combined theoretical insight and practical skills to identify and implement DL architecture for almost any real-world challenge. Learn more about the book here: https://www.manning.com/books/math-and-architectures-of-deep-learning

1. Understanding
the Math behind
the Algorithms
With Math and Architectures of Deep
Learning. Take 42% off by entering
slchaudhury into the discount code box
at checkout at manning.com.

2. The mathematical paradigms
that underpin deep learning
typically start out as dense
academic papers, often leaving
engineers in the dark about how
their models actually function.
Learning mathematical
foundations and neural network
architecture can be challenging,
but the payoff is big.

3. 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.
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.

4. Math and Architectures of Deep
Learning sets out the foundations
of DL in a way that’s both useful
and accessible to working
practitioners.
Each chapter explores a new
fundamental DL concept or
architectural pattern, explaining
the underlying mathematics and
demonstrating how they work in
practice with well-annotated
Python code.

5. What people are saying
about the book:
Gives a unique
perspective about
machine learning
and mathematical
approaches.
-Krzysztof Kamyczek
This is a book that will reward
your patience and perseverance
with a clear and detailed
knowledge of deep learning
mathematics and associated
techniques.
-Tony Holdr

6. About the author:
Krishnendu Chaudhury is a
deep learning and computer
vision expert with decade-long
stints at both Google and
Adobe Systems under his belt.
He is presently CTO and co-
founder of Drishti
Technologies. He has a PhD in
computer science from the
University of Kentucky at
Lexington.

7. Take 42% off Math and Architectures of
Deep Learning by entering slchaudhury
into the discount code box at checkout
at manning.com.
If you want to learn more about the
book, you can check it on our browser-
based liveBook reader here.