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Data Structures in C by Noel Kalicharan
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Jumping into C++
Alex Allain - 2013
As a professional C++ developer and former Harvard teaching fellow, I know what you need to know to be a great C++ programmer, and I know how to teach it, one step at a time. I know where people struggle, and why, and how to make it clear. I cover every step of the programming process, including:Getting the tools you need to program and how to use them*Basic language feature like variables, loops and functions*How to go from an idea to code*A clear, understandable explanation of pointers*Strings, file IO, arrays, references*Classes and advanced class design*C++-specific programming patterns*Object oriented programming*Data structures and the standard template library (STL)Key concepts are reinforced with quizzes and over 75 practice problems.
Practical Statistics for Data Scientists: 50 Essential Concepts
Peter Bruce - 2017
Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data
CISSP Study Guide
Eric Conrad - 2010
The exam is designed to ensure that someone who is handling computer security in a company has a standardized body of knowledge. The book is composed of 10 domains of the Common Body of Knowledge. In each section, it defines each domain. It also provides tips on how to prepare for the exam and take the exam. It also contains CISSP practice quizzes to test ones knowledge. The first domain provides information about risk analysis and mitigation. It also discusses security governance. The second domain discusses different techniques for access control, which is the basis for all the security disciplines. The third domain explains the concepts behind cryptography, which is a secure way of communicating that is understood only by certain recipients. Domain 5 discusses security system design, which is fundamental for operating the system and software security components. Domain 6 is a critical domain in the Common Body of Knowledge, the Business Continuity Planning, and Disaster Recovery Planning. It is the final control against extreme events such as injury, loss of life, or failure of an organization. Domains 7, 8, and 9 discuss telecommunications and network security, application development security, and the operations domain, respectively. Domain 10 focuses on the major legal systems that provide a framework in determining the laws about information system.
R in Action
Robert Kabacoff - 2011
The book begins by introducing the R language, including the development environment. Focusing on practical solutions, the book also offers a crash course in practical statistics and covers elegant methods for dealing with messy and incomplete data using features of R.About the TechnologyR is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data.About the BookR in Action is a language tutorial focused on practical problems. It presents useful statistics examples and includes elegant methods for handling messy, incomplete, and non-normal data that are difficult to analyze using traditional methods. And statistical analysis is only part of the story. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's InsidePractical data analysis, step by stepInterfacing R with other softwareUsing R to visualize dataOver 130 graphsEight reference appendixes================================Table of ContentsPart I Getting startedIntroduction to RCreating a datasetGetting started with graphsBasic data managementAdvanced data managementPart II Basic methodsBasic graphsBasic statisticsPart III Intermediate methodsRegressionAnalysis of variancePower analysisIntermediate graphsRe-sampling statistics and bootstrappingPart IV Advanced methodsGeneralized linear modelsPrincipal components and factor analysisAdvanced methods for missing dataAdvanced graphics
Problem Solving with C++: The Object of Programming
Walter J. Savitch - 1995
It introduces the use of classes; shows how to write ADTs that maximize the perfomance of C++ in creating reusable code; and provides coverage of all important OO functions, including inheritance, polymorphism and encapsulation.
Ambient Findability: What We Find Changes Who We Become
Peter Morville - 2005
Written by Peter Morville, author of the groundbreaking Information Architecture for the World Wide Web, the book defines our current age as a state of unlimited findability. In other words, anyone can find anything at any time. Complete navigability.Morville discusses the Internet, GIS, and other network technologies that are coming together to make unlimited findability possible. He explores how the melding of these innovations impacts society, since Web access is now a standard requirement for successful people and businesses. But before he does that, Morville looks back at the history of wayfinding and human evolution, suggesting that our fear of being lost has driven us to create maps, charts, and now, the mobile Internet.The book's central thesis is that information literacy, information architecture, and usability are all critical components of this new world order. Hand in hand with that is the contention that only by planning and designing the best possible software, devices, and Internet, will we be able to maintain this connectivity in the future. Morville's book is highlighted with full color illustrations and rich examples that bring his prose to life.Ambient Findability doesn't preach or pretend to know all the answers. Instead, it presents research, stories, and examples in support of its novel ideas. Are we truly at a critical point in our evolution where the quality of our digital networks will dictate how we behave as a species? Is findability indeed the primary key to a successful global marketplace in the 21st century and beyond. Peter Morville takes you on a thought-provoking tour of these memes and more -- ideas that will not only fascinate but will stir your creativity in practical ways that you can apply to your work immediately.
Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites
Matthew A. Russell - 2011
You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed.Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools.Get a straightforward synopsis of the social web landscapeUse adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+Learn how to employ easy-to-use Python tools to slice and dice the data you collectExplore social connections in microformats with the XHTML Friends NetworkApply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detectionBuild interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits"A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google
Cryptography Engineering: Design Principles and Practical Applications
Niels Ferguson - 2010
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.
Data Analysis with Open Source Tools: A Hands-On Guide for Programmers and Data Scientists
Philipp K. Janert - 2010
With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora
The Wages of Wins: Taking Measure of the Many Myths in Modern Sport
David J. Berri - 2006
Over the years sports debates have become muddled by many myths that do not match the numbers generated by those playing the games. In The Wages of Wins, the authors use layman's language and easy to follow examples based on their own academic research to debunk many of the most commonly held beliefs about sports.In this updated version of their book, these authors explain why Allen Iverson leaving Philadelphia made the 76ers a better team, why the Yankees find it so hard to repeat their success from the late 1990s, and why even great quarterbacks like Brett Favre are consistently inconsistent. The book names names, and makes it abundantly clear that much of the decision making of coaches and general managers does not hold up to an analysis of the numbers. Whether you are a fantasy league fanatic or a casual weekend fan, much of what you believe about sports will change after reading this book.
The Quick Python Book
Naomi R. Ceder - 2000
This updated edition includes all the changes in Python 3, itself a significant shift from earlier versions of Python.The book begins with basic but useful programs that teach the core features of syntax, control flow, and data structures. It then moves to larger applications involving code management, object-oriented programming, web development, and converting code from earlier versions of Python.True to his audience of experienced developers, the author covers common programming language features concisely, while giving more detail to those features unique to Python.Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.
Data Analysis Using SQL and Excel
Gordon S. Linoff - 2007
This book helps you use SQL and Excel to extract business information from relational databases and use that data to define business dimensions, store transactions about customers, produce results, and more. Each chapter explains when and why to perform a particular type of business analysis in order to obtain useful results, how to design and perform the analysis using SQL and Excel, and what the results should look like.
Mining of Massive Datasets
Anand Rajaraman - 2011
This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on 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. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.
The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios
Steve Wexler - 2017
It's great to have theory and evidenced-based research at your disposal, but what will you do when somebody asks you to make your dashboard 'cooler' by adding packed bubbles and donut charts?The expert authors have a combined 30-plus years of hands-on experience helping people in hundreds of organizations build effective visualizations. They have fought many 'best practices' battles and having endured bring an uncommon empathy to help you, the reader of this book, survive and thrive in the data visualization world.A well-designed dashboard can point out risks, opportunities, and more; but common challenges and misconceptions can make your dashboard useless at best, and misleading at worst. The Big Book of Dashboards gives you the tools, guidance, and models you need to produce great dashboards that inform, enlighten, and engage.