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This book covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single and short book.... Læs mere
Suitable for IT professionals developing Oracle-based Web-enabled applications in PLlSQL, Java, C, C++, .NET, Perl, and PHP, this book focuses on... Læs mere
Based on the author’s experience teaching data science for more than 10 years, Mathematics and R Programming for Machine Learning reveals how machine learning algorithms do their magic and explains how logic can be implemented in code.
Showing test managers what to focus on strategically, tactically, and operationally, this book covers various aspects of test management for those inheriting or starting a test... Læs mere
Written by experienced LabVIEW™ developers and engineers, this guide explains how to integrate LabVIEW into real-life applications. Each chapter... Læs mere
Defines the 2,500 most-used words in the embedded systems field, with over 4,500 entries and cross-references. This dictionary is designed to serve both the technical and non-technical audience.
Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming introduces computational problem solving as a vehicle of discovery in a wide variety of disciplines.
Using the implementation of a deep learning framework as an example, C++ Template Metaprogramming in Practice: A Deep Learning Framework explains the application of metaprogramming in a relatively large project and emphasizes ways to optimize systems performance.
Computer programming is an empowering skill for those who wants to better the world, improve their career, or just have fun. This book covers... Læs mere