Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Computational Methods for Deep Learning: Theoretic, Practice and Applications (Texts in Computer Science)

Buy

Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical models, and algorithmic implementation, as well as covers datasets preparation, programming, results analysis and evaluations.

Beginning with a grounding about artificial neural networks with neurons and the activation functions, the work then explains the mechanism of deep learning using advanced mathematics. In particular, it emphasizes how to use TensorFlow and the latest MATLAB deep-learning toolboxes for implementing deep learning algorithms.

As a prerequisite, readers should have a solid understanding especially of mathematical analysis, linear algebra, numerical analysis, optimizations, differential geometry, manifold, and information theory, as well as basic algebra, functional analysis, and graphical models. This computational knowledge will assist in comprehending the subject matter not only of this text/reference, but also in relevant deep learning journal articles and conference papers.

This textbook/guide is aimed at Computer Science research students and engineers, as well as scientists interested in deep learning for theoretic research and analysis. More generally, this book is also helpful for those researchers who are interested in machine intelligence, pattern analysis, natural language processing, and machine vision.

Dr. Wei Qi Yan is an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title, Visual Cryptography for Image Processing and Security.       



(HTML tags aren't allowed.)

UNDERSTANDING STATISTICS
UNDERSTANDING STATISTICS
This is a book on the understanding of statistical concepts. If you have no knowledge, you will receive basic knowledge, without having to worry much about mathematics. And if you already know something about statistical methods, you will get a better understanding of the ideas behind them. All basic concepts are discussed in detail and...
Interpreting and Visualizing Regression Models Using Stata
Interpreting and Visualizing Regression Models Using Stata

Interpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using polynomials,...

Analyzing Data Through Probabilistic Modeling in Statistics
Analyzing Data Through Probabilistic Modeling in Statistics
"This book addresses different aspects of probabilistic modeling, stochastic methods, probabilistic distributions, data analysis, optimization methods, and probabilistic methods in risk analysis"--...

Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL
Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL

Learn how to accelerate C++ programs using data parallelism. This open access book enables C++ programmers to be at the forefront of this exciting and important new development that is helping to push computing to new levels. It is full of practical advice, detailed explanations, and code examples to illustrate key topics. 

...
Pro Python 3: Features and Tools for Professional Development
Pro Python 3: Features and Tools for Professional Development

Refine your programming techniques and approaches to become a more productive and creative Python programmer. This book explores the concepts and features that will improve not only your code but also your understanding of the Python community with insights and details about the Python philosophy.

Pro Python 3,...

Dive Into Algorithms: A Pythonic Adventure for the Intrepid Beginner
Dive Into Algorithms: A Pythonic Adventure for the Intrepid Beginner
Dive Into Algorithms is a broad introduction to algorithms using the Python Programming Language.

Dive Into Algorithms is a wide-ranging, Pythonic tour of many of the world's most interesting algorithms. With little more than a bit of computer programming experience and basic high-school math,
...
©2021 LearnIT (support@pdfchm.net) - Privacy Policy