But while Metasploit is used by security professionals everywhere, the tool can be hard to grasp for first-time users. Metasploit: The Penetration Tester's Guide fills this gap by teaching you how to harness the Framework and interact with the vibrant community of Metasploit contributors.Once you've built your foundation for penetration testing, you'll learn the Framework's conventions, interfaces, and module system as you launch simulated attacks. You'll move on to advanced penetration testing techniques, including network reconnaissance and enumeration, client-side attacks, wireless attacks, and targeted social-engineering attacks.Learn how to:Find and exploit unmaintained, misconfigured, and unpatched systems Perform reconnaissance and find valuable information about your target Bypass anti-virus technologies and circumvent security controls Integrate Nmap, NeXpose, and Nessus with Metasploit to automate discovery Use the Meterpreter shell to launch further attacks from inside the network Harness standalone Metasploit utilities, third-party tools, and plug-ins Learn how to write your own Meterpreter post exploitation modules and scripts You'll even touch on exploit discovery for zero-day research, write a fuzzer, port existing exploits into the Framework, and learn how to cover your tracks. Whether your goal is to secure your own networks or to put someone else's to the test, Metasploit: The Penetration Tester's Guide will take you there and beyond.

    With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

    As in the original book, Dive Into Python, each chapter starts with a real, complete code sample, proceeds to pick it apart and explain the pieces, and then puts it all back together in a summary at the end.This book includes:Example programs completely rewritten to illustrate powerful new concepts now available in Python 3: sets, iterators, generators, closures, comprehensions, and much more A detailed case study of porting a major library from Python 2 to Python 3 A comprehensive appendix of all the syntactic and semantic changes in Python 3 This is the perfect resource for you if you need to port applications to Python 3, or if you like to jump into languages fast and get going right away.

    Now, 10 years later and in the third edition, this classic still reigns supreme as the book written by an SQL master that teaches future SQL masters. These are not just tips and techniques; Joe also offers the best solutions to old and new challenges and conveys the way you need to think in order to get the most out of SQL programming efforts for both correctness and performance.In the third edition, Joe features new examples and updates to SQL-99, expanded sections of Query techniques, and a new section on schema design, with the same war-story teaching style that made the first and second editions of this book classics.

    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

    Instead they shared with me their "career acumen" secrets, things they wished they had learned at school, but instead have had to learn the hard way..through years of experience. In this book, you will hear these leaders' secrets around: -Finding and using your superpowers , the qualities that make you completely unique and memorable - A script for how to negotiate your salary (in a non-aggressive way) and influence your managers and peers from day one - How to do that infamous "networking" thing everyone talks about, especially if you're not a networking event kind of person - How to have professional presence that sets you apart from everyone else - How to hit the ground running in the first 100 days and be the "rockstar" employee everyone talks about and wishes they could hire more of I've had all kinds of adventures during my 10 years of engineering at Microsoft but my absolute favorite thing has been building relationships, speaking to, and mentoring people (both in and out of the tech industry) on how to achieve their career goals while still being themselves. When I interviewed 25 tech leaders for advice on the questions I get over and over, I wanted to share it with more than just my mentees. This book is full of practical, do-today things as well as "scripts" and email templates that we have all actually used. Read the book and let's talk. I love reaching and meeting new people and you can now consider me “in your network” and I hope I can do the same for you. My best always, Dona

    In this richly illustrated book, accessible examples are used to show how information theory can be understood in terms of everyday games like '20 Questions', and the simple MatLab programs provided give hands-on experience of information theory in action. Written in a tutorial style, with a comprehensive glossary, this text represents an ideal primer for novices who wish to become familiar with the basic principles of information theory.Download chapter 1 from http://jim-stone.staff.shef.ac.uk/Boo...

    Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques.The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner. The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself.

    His revelations demystify the strategy behind the company's recent flurry of bold moves, all driven by the pursuit of a business plan unlike any other: to become the indispensable gatekeeper of all the world's information, the one-stop destination for all our information needs. Will Google succeed? And what are the implications of a single company commanding so much information and knowing so much about us? As ambitious as Google's goal is, with 68 percent of all Web searches (and growing), profits that are the envy of the business world, and a surplus of talent, the company is, Stross shows, well along the way to fulfilling its ambition, becoming as dominant a force on the Web as Microsoft became on the PC. Google isn't just a superior search service anymore. In recent years it has launched a dizzying array of new services and advanced into whole new businesses, from the introductions of its controversial Book Search and the irresistible Google Earth, to bidding for a slice of the wireless-phone spectrum and nonchalantly purchasing YouTube for $1.65 billion. Google has also taken direct aim at Microsoft's core business, offering free e-mail and software from word processing to spreadsheets and calendars, pushing a transformative -- and highly disruptive -- concept known as "cloud computing." According to this plan, users will increasingly store all of their data on Google's massive servers -- a network of a million computers that amounts to the world's largest supercomputer, with unlimited capacity to house all the information Google seeks. The more offerings Google adds, and the more ubiquitous a presence it becomes, the more dependent its users become on its services and the more information they contribute to its uni

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    Most developers have a limited understanding of compositional techniques. It's time for that to change.In "Composing Software", Eric Elliott shares the fundamentals of composition, including both function composition and object composition, and explores them in the context of JavaScript. The book covers the foundations of both functional programming and object oriented programming to help the reader better understand how to build and structure complex applications using simple building blocks.You'll learn: • Functional programming • Object composition • How to work with composite data structures • Closures • Higher order functions • Functors (e.g., array.map) • Monads (e.g., promises) • Transducers • LensesAll of this in the context of JavaScript, the most used programming language in the world. But the learning doesn't stop at JavaScript. You'll be able to apply these lessons to any language. This book is about the timeless principles of software composition and its lessons will outlast the hot languages and frameworks of today. Unlike most programming books, this one may still be relevant 20 years from now.This book began life as a popular blog post series that attracted hundreds of thousands of readers and influenced the way software is built at many high growth tech startups and fortune 500 companies.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    GRAPH THEORY WITH APPLICATIONS TO ENGINEERING AND COMPUTER SCIENCE-PHI-DEO, NARSINGH-1979-EDN-1

    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

    In that time, the data warehouse industry has reached full maturity and acceptance, hardware and software have made staggering advances, and the techniques promoted in the premiere edition of this book have been adopted by nearly all data warehouse vendors and practitioners. In addition, the term business intelligence emerged to reflect the mission of the data warehouse: wrangling the data out of source systems, cleaning it, and delivering it to add value to the business.Ralph Kimball and his colleagues have refined the original set of Lifecycle methods and techniques based on their consulting and training experience. The authors understand first-hand that a data warehousing/business intelligence (DW/BI) system needs to change as fast as its surrounding organization evolves. To that end, they walk you through the detailed steps of designing, developing, and deploying a DW/BI system. You'll learn to create adaptable systems that deliver data and analyses to business users so they can make better business decisions.