Frank Luna has been programming interactive 3D graphics with DirectX for more than fifteen years. He is the author of three bestselling books on DirectX and has worked in 3D medical visualization, 3D architectural design software, and gaming. He hol
mplement state-of-the-art techniques to visualize solutions to challenging problems in scientific computing, with the use of the SciPy stack. About This Book Master the theory and algorithms behind numerical recipes and how they can be applied to re
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Book Descr iption: Since their introduction to Unity, Shaders have been notoriously difficult to understand and implement in games: complex mathematics have always stood in the way of creating your own Shaders and attaining that level of realism you
Magma is a large, well-supported software package designed for computations in algebra, number theory, algebraic geometry and algebraic combinatorics. It provides a mathematically rigorous environment for defining and working with structures such as
Gauss's law for electric fields, Gauss's law for magnetic fields, Faraday's law, and the Ampere-Maxwell law are four of the most influential equations in science. In this guide for students, each equation is the subject of an entire chapter, with de
Key Features Perform data analysis and build predictive models on huge datasets that leverage Apache Spark Learn to integrate data science algorithms and techniques with the fast and scalable computing features of Spark to address big data challenge
This book explains the broad topic of automated trading, starting with its mathematics and moving to its computation and execution. Readers will gain a unique insight into the mechanics and computational considerations taken in building a backtester
Summary Real-World Machine Learning is a practical guide designed to teach working developers the art of ML project execution. Without overdosing you on academic theory and complex mathematics, it introduces the day-to-day practice of machine learni
This book explains the broad topic of automated trading, starting with its mathematics and moving to its computation and execution. Readers will gain a unique insight into the mechanics and computational considerations taken in building a backtester
Most of the examples are relevant for computational science. This means that the examples have a root in mathematical subjects, but the amount of mathematical details is kept as low as possible to enlarge the audience and allow focusing on software
This book is inspired by the Machine Learning Model Building Process Flow, which provides the reader the ability to understand a ML algorithm and apply the entire process of building a ML model from the raw data. This new paradigm of teaching Machin
This textbook on practical data analytics unites fundamental principles, algorithms, and data. Algorithms are the keystone of data analytics and the focal point of this textbook. Clear and intuitive explanations of the mathematical and statistical f
This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It provides desc
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamen
This introduction to 3D computer graphics emphasizes fundamentals and the mathematics underlying computer graphics, while also covering programming techniques using OpenGL, a platform-independent graphics programming environment. The minimal prerequ
