The SY0-301 version covers every aspect of the SY0-301 exam, and includes the same elements readers raved about in the previous version. Each of the eleven chapters presents topics in an easy to understand manner and includes real-world examples of security principles in action. The author uses many of the same analogies and explanations he's honed in the classroom that have helped hundreds of students master the Security+ content. You'll understand the important and relevant security topics for the Security+ exam, without being overloaded with unnecessary details. Additionally, each chapter includes a comprehensive review section to help you focus on what's important. Over 450 realistic practice test questions with in-depth explanations will help you test your comprehension and readiness for the exam. The book includes a 100 question pre-test, a 100 question post-test, and practice test questions at the end of every chapter. Each practice test question includes a detailed explanation to help you understand the content and the reasoning behind the question. You'll be ready to take and pass the exam the first time you take it. If you plan to pursue any of the advanced security certifications, this guide will also help you lay a solid foundation of security knowledge. Learn this material, and you'll be a step ahead for other exams. This SY0-301 study guide is for any IT or security professional interested in advancing in their field, and a must read for anyone striving to master the basics of IT systems security. The author supplements the book with blog posts here: http: //blogs.getcertifiedgetahead.com/. This page provides a full listing of mobile device apps from the author: http: //learnzapp.com/partners/darrilgibson/

    The library is not self-explanatory or fully consistent, and there are still some traps for the unwary. But the advantages far outweigh the problems, especially if you've got an expert book like Nicolai Josuttis' C++ Standard Library to help you. Josuttis starts with an overview of the standard library, and its key interrelationships with the core language. He presents detailed coverage of the STL, the most powerful, complex, and exciting part of the library; then covers special containers, strings, numeric classes, and internationalization; and helps you get more out of a component you're probably already using: the IOStream library. Every component description includes purpose, design, code examples, practical scenarios, pitfalls, and in most cases, reference sources. Whether you need a tutorial or reference, this book delivers the goods.— (Bill Camarda, bn.com, editor)

    It aims to give readers a fundamental overview of the technologies that make up the telecommunications infrastructure.

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    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

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    It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX.Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.

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    QED--the edited version of four lectures on quantum electrodynamics that Feynman gave to the general public at UCLA as part of the Alix G. Mautner Memorial Lecture series--is perhaps the best example of his ability to communicate both the substance and the spirit of science to the layperson.The focus, as the title suggests, is quantum electrodynamics (QED), the part of the quantum theory of fields that describes the interactions of the quanta of the electromagnetic field-light, X rays, gamma rays--with matter and those of charged particles with one another. By extending the formalism developed by Dirac in 1933, which related quantum and classical descriptions of the motion of particles, Feynman revolutionized the quantum mechanical understanding of the nature of particles and waves. And, by incorporating his own readily visualizable formulation of quantum mechanics, Feynman created a diagrammatic version of QED that made calculations much simpler and also provided visual insights into the mechanisms of quantum electrodynamic processes.In this book, using everyday language, spatial concepts, visualizations, and his renowned "Feynman diagrams" instead of advanced mathematics, Feynman successfully provides a definitive introduction to QED for a lay readership without any distortion of the basic science. Characterized by Feynman's famously original clarity and humor, this popular book on QED has not been equaled since its publication.

    In chapters that follow, detailed topic reviews cover polynomial, trigonometric, exponential, logarithmic, and rational functions; coordinate and three-dimensional geometry; numbers and operations; data analysis, statistics, and probability; and graphing calculators, their operations and applications. Six full-length model tests with answers, explanations, and self-evaluation charts conclude this manual.

    Combining practical, theoretical, and historical, this book is a must for graphic artists, editors, or anyone working with the printed page using digital or traditional methods.Having established itself as a standard in its field The Elements of Typographic Style is house manual at most American university presses, a standard university text, and a reference work in studios of designers around the world. It has been translated into italian and greek, and dutch.

    Cases, examples and problems from a variety of project types are used to illustrate the text.