Provides the reader with a fundamental understanding of global illumination algorithms. This book discusses a class of algorithms for realistic image synthesis and introduces a theoretical basis for the algorithms presented. It includes: exercises for each chapter; and material on human perception.
Comprehensive survey of artificial intelligence -- the study of how computers can be made to act intelligently. Includes introductory and advanced material. Extensive notes updating the main text. 132 illustrations.
As data hiding detection and forensic techniques have matured, people are creating more advanced stealth methods for spying, corporate espionage, terrorism, and cyber warfare all to avoid detection. Data Hiding provides an exploration into the present day and next generation of tools and techniques used in covert communications, advanced malware methods and data concealment tactics. The hiding techniques outlined include the latest technologies including mobile devices, multimedia, virtualization and others. These concepts provide corporate, goverment and military personnel with the knowledge to investigate and defend against insider threats, spy techniques, espionage, advanced malware and secret communications. By understanding the plethora of threats, you will gain an understanding of the methods to defend oneself from these threats through detection, investigation, mitigation and prevention. Provides many real-world examples of data concealment on the latest technologies including iOS, Android, VMware, MacOS X, Linux and Windows 7 Dives deep into the less known approaches to data hiding, covert communications, and advanced malware Includes never before published information about next generation methods of data hiding Outlines a well-defined methodology for countering threats Looks ahead at future predictions for data hiding
This book provides a theoretical and application-oriented analysis of deterministic scheduling problems in advanced planning and computer systems. The text examines scheduling problems across a range of parameters: job priority, release times, due dates, processing times, precedence constraints, resource usage and more, focusing on such topics as computer systems and supply chain management. Discussion includes single and parallel processors, flexible shops and manufacturing systems, and resource-constrained project scheduling. Many applications from industry and service operations management and case studies are described. The handbook will be useful to a broad audience, from researchers to practitioners, graduate and advanced undergraduate students.
Get up to speed on Git for tracking, branching, merging, and managing code revisions. Through a series of step-by-step tutorials, this practical guide takes you quickly from Git fundamentals to advanced techniques, and provides friendly yet rigorous advice for navigating the many functions of this open source version control system. This thoroughly revised edition also includes tips for manipulating trees, extended coverage of the reflog and stash, and a complete introduction to the GitHub repository. Git lets you manage code development in a virtually endless variety of ways, once you understand how to harness the system´s flexibility. This book shows you how. Learn how to use Git for several real-world development scenarios Gain insight into Git´s common-use cases, initial tasks, and basic functions Use the system for both centralized and distributed version control Learn how to manage merges, conflicts, patches, and diffs Apply advanced techniques such as rebasing, hooks, and ways to handle submodules Interact with Subversion (SVN) repositories - including SVN to Git conversions Navigate, use, and contribute to open source projects though GitHub
This book describes established and advanced methods for reducing the dimensionality of numerical databases. Each description starts from intuitive ideas, develops the necessary mathematical details, and ends by outlining the algorithmic implementation. The text provides a lucid summary of facts and concepts relating to well-known methods as well as recent developments in nonlinear dimensionality reduction. Methods are all described from a unifying point of view, which helps to highlight their respective strengths and shortcomings. The presentation will appeal to statisticians, computer scientists and data analysts, and other practitioners having a basic background in statistics or computational learning.
KEY SELLING POINTS Includes coverage of the brand-new TI-84 Plus CE For TI-83 Plus and TI-84 Plus series of graphing calculators The ´´missing manual´´ for the TI-84 Plus calculators Gets readers up and running on calculators fast Fun, engaging, and approachable examples Easy hands-on learn by doing approach AUDIENCE This book is written for students, teachers?anyone who wants to use the TI-84 Plus or TI-83 Plus of graphing calculators. No prior experience is needed and it assumes no advanced knowledge of math and science.
Think, ´´Kanban in a box.? Imagine you ordered Kanban for your team, and got the box delivered to your door. You open the box and right on top is a quick-start guide. Being a novice, you follow the guide, and quickly get up and running. As you become more experienced, the other box contents address common advanced issues you´d face, like right-sizing teams, estimation, hitting deadlines, transitioning from Scrum or Waterfall, deploying components and services, and using Kanban within larger organizations.
This concise, accessible text provides a thorough introduction to quantum computing - an exciting emergent field at the interface of the computer, engineering, mathematical and physical sciences. Aimed at advanced undergraduate and beginning graduate students in these disciplines, the text is technically detailed and is clearly illustrated throughout with diagrams and exercises. Some prior knowledge of linear algebra is assumed, including vector spaces and inner products. However, prior familiarity with topics such as tensor products and spectral decomposition is not required, as the necessary material is reviewed in the text.
Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You´ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and Swish), seeing how to perform linear and logistic regression using TensorFlow, and choosing the right cost function. The next section talks about more complicated neural network architectures with several layers and neurons and explores the problem of random initialization of weights. An entire chapter is dedicated to a complete overview of neural network error analysis, giving examples of solving problems originating from variance, bias, overfitting, and datasets coming from different distributions. Applied Deep Learning also discusses how to implement logistic regression completely from scratch without using any Python library except NumPy, to let you appreciate how libraries such as TensorFlow allow quick and efficient experiments. Case studies for each method are included to put into practice all theoretical information. You´ll discover tips and tricks for writing optimized Python code (for example vectorizing loops with NumPy). What You Will Learn Implement advanced techniques in the right way in Python and TensorFlow Debug and optimize advanced methods (such as dropout and regularization) Carry out error analysis (to realize if one has a bias problem, a variance problem, a data offset problem, and so on) Set up a machine learning project focused on deep learning on a complex dataset Who This Book Is For Readers with a medium understanding of machine learning, linear algebra, calculus, and basic Python programming.