“…The steady focus throughout the book is on how to turn the mathematical artefacts and specialist jargon that are second nature to statisticians into plain English for corporate customers and stakeholders. …”

“…He received a M.S. in computer science from Syracuse University, and a Ph.D. in mathematics from the University of Michigan in Ann Arbor. …”

“…A basic knowledge of mathematics is needed to understand the various methods that are used or created during the course of the book to exploit the capabilities that Julia is designed with. …”

“…What You Will Learn Understand physically based rendering to fit the aesthetic of your game Write shaders from scratch in ShaderLab and HLSL/Cg Combine shader programming with interactive scripts to add life to your materials Design efficient shaders for mobile platforms without sacrificing their realism Use state-of-the-art techniques, such as volumetric explosions and fur shading Master the math and algorithms behind the most used lighting models Understand how shader models have evolved and how you can create your own In Detail Since their introduction to Unity, shaders have been seen as notoriously difficult to understand and implement in games. Complex mathematics has always stood in the way of creating your own shaders and attaining the level of realism you crave. …”

“…Once you've got to grips with the fundamental mathematical principles, you'll start exploring neural networks and identify how to tackle challenges in large networks using advanced algorithms. …”

“…Prior knowledge of C++ and familiarity with mathematical concepts will help you better ..…”

“…Should be familiar with mathematics (basic operations and coordinate systems) and game elements (players, scores, enemies, etc.). …”

“…It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on. …”

“…Master the linear algebra and other mathematical skills you'll need Explore key physics ideas, such as quantum states and uncertainty Review data structures, algorithms, and computing complexity Work with probability and set theory in quantum computing Familiarize yourself with basic quantum theory and formulae Understand quantum entanglement and quantum key distribution Discover how quantum computers are architected and built Explore several leading quantum algorithms Compare quantum and conventional asymmetric algorithms See how quantum computing might break traditional cryptography Discover several approaches to quantum-resistant cryptography Start coding with Q#, Microsoft's quantum programming language Simulate quantum gates and algorithms with QASM If you prefer a multimodal approach to learning, check out the Quantum Computing Fundamentals book by Chuck Easttom!…”

“…He has a solid and successful track record of teaching mathematics and web development…”

“…Although not a prerequisite, a solid theoretical understanding of mathematics for deep learning will be beneficial…”

“…The activity is resource hungry, and it behoves us to do the best we can to present the best possible experience to our students.•Henderson et al. consider the issue of mathematics in the curriculum. Uttering the word "maths" in most staff common rooms is like hitting a raw nerve, and the Group have done a good job of surveying the role and place of maths in the curriculum, and how attitudes are changing.•McCracken et al. consider the actual programming fluency o f our students after we have taught them. …”

“…Learn how to apply powerful data analysis techniques with popular open source Python modules About This Book Find, manipulate, and analyze your data using the Python 3.5 libraries Perform advanced, high-performance linear algebra and mathematical calculations with clean and efficient Python code An easy-to-follow guide with realistic examples that are frequently used in real-world data analysis projects. …”

“…About This Book Explore and create intelligent systems using cutting-edge deep learning techniques Implement deep learning algorithms and work with revolutionary libraries in Python Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and more Who This Book Is For This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired. …”

“…The biomedical research community has been slow to integrate computer aided modeling & simulation for many reasons: including the perception that biology and pharmacology are "too complex" and "too variable" to be modeled with mathematical equations; a lack of adequate graduate training programs; and the lack of support from government agencies that fund biomedical research. …”

“…The anomaly detection techniques and examples in this book combine psychology, statistics, mathematics, and Python programming in a way that is easily accessible to software developers. …”

“…No matter your motivation or current job role, this course helps you: Learn subnetting: Understand the ideas and terms in each part of IPv4 subnetting, how to use the ideas in the related mathematical processes, and the purpose and meaning of the facts learned by those processes. …”

“…It takes the complexity of mathematical Set Theory and of First Order Predicate Logic, as outlined in E. …”

“…Part III focuses on building an application called MathPaper, which is similar to a word processor but which instead solves mathematical expressions the user supplies. The chapters in this part of the book extend MathPaper by developing both the front and back ends using a variety of Cocoa classes and methods. …”

“…Skill Level All Levels What You Will Learn OpenGL 4.4 API essentials How to write shaders using OpenGL Shading Language (GLSL) The 3D mathematics behind 3D graphics How to load and render 3D models Mapping textures to 3D objects Ambient and diffuse lighting, specular highlights, point lights, and spotlights Environment mapping, fog, normal mapping, and color blending Survey additional topics in modern rendering, including post processing, shadow mapping, skeletal animation, geometry and tessellation shaders, deferred rendering, global illumination, and compute shaders. …”