By the end of the book, you'll understand how to develop a large, maintainable, and performant application with AngularJS.Guided by two engineers who worked on AngularJS at Google, you'll learn the components needed to build data-driven applications, using declarative programming and the Model-view-controller pattern. You'll also learn how to conduct unit tests on each part of your application.Learn how to use controllers for moving data to and from viewsUnderstand when to use AngularJS services instead of controllersCommunicate with the server to store, fetch, and update data asynchronouslyKnow when to use AngularJS filters for converting data and values to different formatsImplement single-page applications, using ngRoute to select views and navigationDive into basic and advanced directives for creating reusable componentsWrite an end-to-end test on a live version of your entire applicationUse best practices, guidelines, and tools throughout the development cycle

    It is offered for sale in print format as a convenience.Get a head start evaluating Windows Azure - with technical insights from a Microsoft MVP Mitch Tulloch. This guide introduces the latest features and capabilities, with scenario-based advice on how the platform can meet the needs of your business. Get the high-level overview you need to begin preparing your deployment now.Topics include: Understanding Windows Azure Windows Azure Compute Services Windows Azure Network Services Windows Azure Data Services Windows Azure App Services Getting Started with Windows Azure

    Beginners and intermediate developers will appreciate the comprehensive tutorial that walks step-by-step through building a real client/server database, from concept to deployment and beyond -- and points out key pitfalls to avoid throughout the process. Experienced users will appreciate the book's comprehensive coverage of the Transact-SQL language, from basic to advanced level; detailed ODBC database access information; expert coverage of concurrency control, and more. The book includes thorough, up-to-the-minute guidance on building multi-tier applications; SQL Server performance tuning; and other crucial issues for advanced developers. For all database developers, system administrators, and Web application developers who interact with databases in Microsoft-centric environments.

    With this long-awaited revision, the authors continue to present the theory in a concise and straightforward manner, now with an eye out for the practical applications. They have revised this book to make it more accessible to today's students, including the addition of more material on writing proofs, more figures and pictures to convey ideas, side-boxes to highlight other interesting material, and a less formal writing style. Exercises at the end of each chapter, including some new, easier exercises, help readers confirm and enhance their understanding of the material. *NEW! Completely rewritten to be less formal, providing more accessibility to todays students. *NEW! Increased usage of figures and pictures to help convey ideas. *NEW! More detail and intuition provided for definitions and proofs. *NEW! Provides special side-boxes to present supplemental material that may be of interest to readers. *NEW! Includes more exercises, including many at a lower level. *NEW! Presents program-like notation for PDAs and Turing machines. *NEW! Increas

    Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of exercises, case studies, and easy-to-understand explanations.You’ll work with graphs, algorithm analysis, scale-free networks, and cellular automata, using advanced features that make Python such a powerful language. Ideal as a text for courses on Python programming and algorithms, Think Complexity will also help self-learners gain valuable experience with topics and ideas they might not encounter otherwise.Work with NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tablesStudy abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machinesGet starter code and solutions to help you re-implement and extend original experiments in complexityExplore the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, and other topicsExamine case studies of complex systems submitted by students and readers

    

    This classic guide—fully updated for Windows Server 2003, Windows XP, and Windows 2000, including 64-bit extensions—describes the architecture and internals of the Windows operating system. You’ll find hands-on experiments you can use to experience Windows internal behavior firsthand, along with advanced troubleshooting information to help you keep your systems running smoothly and efficiently. Whether you’re a developer or a system administrator, you’ll find critical architectural insights that you can quickly apply for better design, debugging, performance, and support.Get in-depth, inside knowledge of the Windows operating system: Understand the key mechanisms that configure and control Windows, including dispatching, startup and shutdown, and the registry Explore the Windows security model, including access, privileges, and auditing Investigate internal system architecture using the kernel debugger and other tools Examine the data structures and algorithms that deal with processes, threads, and jobs Observe how Windows manages virtual and physical memory Understand the operation and format of NTFS, and troubleshoot file system access problems View the Windows networking stack from top to bottom, including mapping, APIs, name resolution, and protocol drivers Troubleshoot boot problems and perform crash analysis

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

    Servers give sysadmins a incredible visibility into the network—once they know how to unlock it. Most sysadmins don’t need to understand window scaling, or the differences between IPv4 and IPv6 echo requests, or other intricacies of the TCP/IP protocols. You need only enough to deploy your own applications and get easy support from the network team.This book teaches you:•How modern networks really work•The essentials of TCP/IP•The next-generation protocol, IPv6•The right tools to diagnose network problems, and how to use them•Troubleshooting everything from the physical wire to DNS•How to see the traffic you send and receive•Connectivity testing•How to communicate with your network team to quickly resolve problemsA systems administrator doesn’t need to know the innards of TCP/IP, but knowing enough to diagnose your own network issues transforms a good sysadmin into a great one.

    Sipser's candid, crystal-clear style allows students at every level to understand and enjoy this field. His innovative "proof idea" sections explain profound concepts in plain English. The new edition incorporates many improvements students and professors have suggested over the years, and offers updated, classroom-tested problem sets at the end of each chapter.

    Johnson. It was the first book exclusively on the theory of NP-completeness and computational intractability. The book features an appendix providing a thorough compendium of NP-complete problems (which was updated in later printings of the book). The book is now outdated in some respects as it does not cover more recent development such as the PCP theorem. It is nevertheless still in print and is regarded as a classic: in a 2006 study, the CiteSeer search engine listed the book as the most cited reference in computer science literature.

    Cryptography is vital to keeping information safe, in an era when the formula to do so becomes more and more challenging. Written by a team of world-renowned cryptography experts, this essential guide is the definitive introduction to all major areas of cryptography: message security, key negotiation, and key management. You'll learn how to think like a cryptographer. You'll discover techniques for building cryptography into products from the start and you'll examine the many technical changes in the field.After a basic overview of cryptography and what it means today, this indispensable resource covers such topics as block ciphers, block modes, hash functions, encryption modes, message authentication codes, implementation issues, negotiation protocols, and more. Helpful examples and hands-on exercises enhance your understanding of the multi-faceted field of cryptography.An author team of internationally recognized cryptography experts updates you on vital topics in the field of cryptography Shows you how to build cryptography into products from the start Examines updates and changes to cryptography Includes coverage on key servers, message security, authentication codes, new standards, block ciphers, message authentication codes, and more Cryptography Engineering gets you up to speed in the ever-evolving field of cryptography.

    Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center.Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel, it is a joy to read. Tim Roughgarden Stanford University

     Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.