Contents
Chapter 1: Fundamentals
Programming Model
Data Abstraction
Bags, Stacks, and Queues
Analysis of Algorithms
Case Study: Union-Find
Chapter 2: Sorting
Elementary Sorts
Mergesort
Quicksort
Priority Queues
Applications
Chapter 3: Searching
Symbol Tables
Binary Search Trees
Balanced Search Trees
Hash Tables
Applications
Chapter 4: Graphs
Undirected Graphs
Directed Graphs
Minimum Spanning Trees
Shortest Paths
Chapter 5: Strings
String Sorts
Tries
Substring Search
Regular Expressions
Data Compression
This newly expanded and the updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students.
The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography.
The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software. In her bestselling guide, Julie Pallant guides you through the entire research process, helping you choose the right data analysis technique for your project. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic and advanced statistical techniques. She outlines each technique clearly, with step-by-step procedures for performing the analysis, a detailed guide to interpreting data output and an example of how to present the results in a report. For both beginners and experienced users in psychology, sociology, health sciences, medicine, education, business and related disciplines, the SPSS Survival Manual is an essential text. Illustrated with screen grabs, examples of output and tips, it is supported by a website with sample data and guidelines on report writing. This sixth edition is fully revised and updated to accommodate changes to IBM SPSS procedures, screens and output.
From elicitation, pretexting, influence and manipulation all aspects of social engineering are picked apart, discussed and explained by using real world examples, personal experience and the science behind them to unraveled the mystery in social engineering.
Kevin Mitnick—one of the most famous social engineers in the world—popularized the term “social engineering.” He explained that it is much easier to trick someone into revealing a password for a system than to exert the effort of hacking into the system. Mitnick claims that this social engineering tactic was the single-most effective method in his arsenal. This indispensable book examines a variety of maneuvers that are aimed at deceiving unsuspecting victims, while it also addresses ways to prevent social engineering threats.
More than 50 percent new and revised content for today's Linux environment gets you up and running in no time!
Linux continues to be an excellent, low-cost alternative to expensive operating systems. Whether you're new to Linux or need a reliable update and reference, this is an excellent resource. Veteran bestselling author Christopher Negus provides a complete tutorial packed with major updates, revisions, and hands-on exercises so that you can confidently start using Linux today. * Offers a complete restructure, complete with exercises, to make the book a better learning tool * Places a strong focus on the Linux command line tools and can be used with all distributions and versions of Linux * Features in-depth coverage of the tools that a power user and a Linux administrator need to get started
Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing.
If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.
Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.
OCA, Oracle Certified Associate Java SE 8 Programmer I Study Guide, Exam 1Z0-808 is a comprehensive study guide for those taking the Oracle Certified Associate Java SE 8 Programmer I exam (1Z0-808). With complete coverage of 100% of the exam objectives, this book provides everything you need to know to confidently take the exam. The release of Java 8 brought the language's biggest changes to date, and for the first time, candidates are required to learn functional programming to pass the exam. This study guide has you covered, with thorough functional programming explanation and information on all key topic areas Java programmers need to know. You'll cover Java inside and out, and learn how to apply it efficiently and effectively to create solutions applicable to real-world scenarios.
Until recently, many people thought big data was a passing fad. "Data science" was an enigmatic term. Today, big data is taken seriously, and data science is considered downright sexy. With this anthology of reports from award-winning journalist Mike Barlow, you’ll appreciate how data science is fundamentally altering our world, for better and for worse.
Barlow paints a picture of the emerging data space in broad strokes. From new techniques and tools to the use of data for social good, you’ll find out how far data science reaches.
With this anthology, you’ll learn how:
This is the of the programming language-independent text that helped establish computer algorithms as a discipline of computer science. The text incorporates the latest research and state-of-the-art applications, bringing this classic to the forefront of modern computer science education. A major strength of this text is its focus on design techniques rather than on individual algorithms. This book is appropriate as a core text for upper-and graduate-level courses in algorithms.
A best-selling book, it provides an accessible introduction to computer hardware and architecture. This book takes a modern structured, layered approach to understanding computer systems. The new edition has been thoroughly updated to reflect today's most critical new technologies and the latest developments in computer organization and architecture. It is specifically written for undergraduate students of computer science. It also serves as a useful resource for all computer professionals and engineers who need an overview or introduction to computer architecture.
Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining.
Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research.
Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge.
Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas. Principles of Data Mining explains and explores the principal techniques of Data Mining: for classification, association rule mining and clustering. Each topic is clearly explained and illustrated by detailed worked examples, with a focus on algorithms rather than mathematical formalism. It is written for readers without a strong background in mathematics or statistics, and any formulae used are explained in detail. This second edition has been expanded to include additional chapters on using frequent pattern trees for Association Rule Mining, comparing classifiers, ensemble classification and dealing with very large volumes of data.
Fortunately for you, there's Schaum's Outlines. More than 40 million students have trusted Schaum's to help them succeed in the classroom and on exams. Schaum's is the key to faster learning and higher grades in every subject. Each Outline presents all the essential course information in an easy-to-follow, topic-by-topic format. You also get hundreds of examples, solved problems, and practice exercises to test your skills.
Modern coverage of the fundamentals, implementation and applications of digital signal processing techniques from a practical point of view.
The past ten years has seen a significant growth in DSP applications throughout all areas of technology and this growth is expected well into the next millennium. This successful textbook covers most aspects of DSP found in undergraduate electrical, electronic or communications engineering courses. Unlike many other texts, it also covers a number of DSP techniques which are of particular relevance to the industry such as adaptive filtering and multirate processing. The emphasis throughout the book is on the practical aspects of DSP.
Wireless Communications provides a self-contained all encompassing current treatment of the area and topics covered will include directional channel modeling, multi-user detection, MIMO systems, and 3G standards. In addition, the author has combined mathematical derivations with intuitive explanations of the physical facts in order to help students (including self-study readers) to acquire a deeper understanding of the facts.
This edition of Curt White's top-selling text maintains a balanced approach between the technical and the practical aspects of data communications, providing a solid understanding not only of how things work, but how they can be applied to create business solutions. Updated to reflect new technologies, this text covers current concepts such as voice over wireless LAN, convergence, MPLS, and PPP, while maintaining the pedagogical elements that have been successful for students in the past.
Operations Research is a comprehensive book for undergraduate mechanical, industrial production and computer science engineers. The book explains how the science of operations research evolved out of the studies conducted during World War 2 and discusses the techniques and their applications to mass production and process flows. The book discusses how to use techniques such as PERT and CPM, as well as how to solve questions based on the traveling salesman problem. It contains a large number of solved and unsolved problems which cover all types of questions posed in the examinations and helps students understand how to solve them. The book is a must-have for all GATE aspirants.
The text goes beyond the standard coverage in operating systems courses with key chapters on multiprocessing, networking, distributed systems, performance, and security. The text features extensive, up-to-the-minute case studies on the latest versions of Linux (2.6) and Microsoft Windows XP. An abundance of charts, diagrams, illustrations and exercises (both with and without solutions) is included.
As enterprises move to implement Service Oriented Architecture (SOA), they increasingly recognize that SOA will only meet its potential if it can be governed well. SOA Governance responds to this crucial realization. In this book, a team of IBM's leading SOA governance experts share hard-won best practices for effectively governing IT in any service-oriented environment. The authors begin by reviewing SOA's promised benefits, and identifying inadequate governance as a root cause when SOA fails. Next, they introduce a comprehensive SOA governance model that works. They define what must be governed, identify key stakeholders, and review the relationship of SOA governance to existing governance bodies, and to processes like CoBIT and ITIL. In Part II, they walk through SOA governance assessment and planning, helping readers identify and fix gaps, set goals and objectives, and establish workable roadmaps. Finally, they turn to the details of "building out" an SOA governance model: establishing authority chains, roles, responsibilities, policies, standards, mechanisms, procedures, and metrics. Along the way, the authors illuminate the unique issues associated applying IT governance to a services model - including the challenges of compliance auditing where service behavior can be unpredictable. They also show why services governance requires a more organizational, business-centric focus than "conventional" IT governance - and how to successfully achieve that focus. For Sale in Indian subcontinent only
