Author Michael Bazzell has been well known in government circles for his ability to locate personal information about anyone through the internet. In Hiding from the Internet: Eliminating Personal Online Information, he exposes the resources that broadcast your personal details to public view. He has researched each source and identified the best method to have your private details removed from the databases that store profiles on all of us. This book will serve as a reference guide for anyone that values privacy. Each technique is explained in simple steps. It is written in a hands-on style that encourages the reader to execute the tutorials as they go. The author provides personal experiences from his journey to disappear from public view. Much of the content of this book has never been discussed in any publication. Always thinking like a hacker, the author has identified new ways to force companies to remove you from their data collection systems. This book exposes loopholes that create unique opportunities for privacy seekers. Among other techniques, you will learn to: Remove your personal information from public databases and people search sites Create free anonymous mail addresses, email addresses, and telephone numbers Control your privacy settings on social networks and remove sensitive data Provide disinformation to conceal true private details Force data brokers to stop sharing your information with both private and public organizations Prevent marketing companies from monitoring your browsing, searching, and shopping habits Remove your landline and cellular telephone numbers from online websites Use a credit freeze to eliminate the worry of financial identity theft and fraud Change your future habits to promote complete privacy and anonymity Conduct a complete background check to verify proper information removalConfigure a home firewall with VPN Kill-SwitchPurchase a completely invisible home or vehicle

    Gain a deep understanding of the “what, why, how, when, how much” questions of your life. Become a Systems Thinker and discover how to approach your life from a completely new perspective. What is systems thinking? Put it simply, thinking about how things interact with one another. Why should this matter to you? Because you are a system. You are a part of smaller and larger systems – your community, your country, your species. Understanding your role within these systems and how these systems affect, hinder, or aid the fulfillment of your life can lead you to better answers about yourself and the world. Information is the most precious asset these days. Evaluating that information correctly is almost priceless. Systems thinkers are some of the bests in collecting and assessing information, as well as creating impactful solutions in any context. The Systems Thinker will help you to implement systems thinking at your workplace, human relations, and everyday thinking habits. Boost your observation and analytical skills to find the real triggers and influencing forces behind contemporary politics, economics, health, and education changes. Systems thinking clears your vision by teaching you not only to find the differences between the elements but also the similarities. This bi-directional analyzing ability will give you a more complex worldview, deeper understanding of problems, and thus better solutions. The car stopped because its tank is empty – so it needs gas. Easy problem, easy solution, right? But could you explain just as easily why did the price of gas raise with 5% the past month? After becoming a systems thinker, you’ll be able to answer that question just as easily. Change your thoughts, change your results. •What are the main elements, questions and methods of thinking in systems? •The most widely used systems archetypes, maps, models, and analytical methods. •Learn to identify and provide solutions even the most complex system problems. •Deepen your understanding about human motivation with systems thinking. The past fifty years brought so many changes in our lives. The world has become more interconnected than ever. Old rules can’t explain the new world anymore. But systems thinking can. Embrace systems thinking and become a master of analytical, critical, and creative thinking.

    -Unprecedented access behind "Half-Life" and "Half-Life 2" -A forward by Valve founder Gabe Newell -Hundreds of art, design, preproduction, and other art pieces crammed into the book -Over a dozen key members of Valve's staff interviewed -Officially approved by Valve -Behind City 17 and other locations -The development of the Source engine -A rogue's gallery of beasts, characters, and monstrosities -Key weapons development revelations -A tour of many of the game's locations, from inception to completion -Filled with art, screens, and anecdotes from the Valve team

    In this handbook, data expert Q. Ethan McCallum has gathered 19 colleagues from every corner of the data arena to reveal how they’ve recovered from nasty data problems.From cranky storage to poor representation to misguided policy, there are many paths to bad data. Bottom line? Bad data is data that gets in the way. This book explains effective ways to get around it.Among the many topics covered, you’ll discover how to:Test drive your data to see if it’s ready for analysisWork spreadsheet data into a usable formHandle encoding problems that lurk in text dataDevelop a successful web-scraping effortUse NLP tools to reveal the real sentiment of online reviewsAddress cloud computing issues that can impact your analysis effortAvoid policies that create data analysis roadblocksTake a systematic approach to data quality analysis

    This practical guide not only shows you how to search, analyze, and explore data with Elasticsearch, but also helps you deal with the complexities of human language, geolocation, and relationships.If you're a newcomer to both search and distributed systems, you'll quickly learn how to integrate Elasticsearch into your application. More experienced users will pick up lots of advanced techniques. Throughout the book, you'll follow a problem-based approach to learn why, when, and how to use Elasticsearch features.Understand how Elasticsearch interprets data in your documentsIndex and query your data to take advantage of search concepts such as relevance and word proximityHandle human language through the effective use of analyzers and queriesSummarize and group data to show overall trends, with aggregations and analyticsUse geo-points and geo-shapes--Elasticsearch's approaches to geolocationModel your data to take advantage of Elasticsearch's horizontal scalabilityLearn how to configure and monitor your cluster in production

    "Machine learning," the process of automating tasks once considered the domain of highly-trained analysts and mathematicians, is the key to efficiently extracting useful information from this sea of raw data. Machine Learning in Action is a unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. In it, the author uses the flexible Python programming language to show how to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification.

    This guide also teaches you safe and practical ways to scale applications through replication, load balancing, high availability, and failover. Updated to reflect recent advances in MySQL and InnoDB performance, features, and tools, this third edition not only offers specific examples of how MySQL works, it also teaches you why this system works as it does, with illustrative stories and case studies that demonstrate MySQL’s principles in action. With this book, you’ll learn how to think in MySQL. Learn the effects of new features in MySQL 5.5, including stored procedures, partitioned databases, triggers, and views Implement improvements in replication, high availability, and clustering Achieve high performance when running MySQL in the cloud Optimize advanced querying features, such as full-text searches Take advantage of modern multi-core CPUs and solid-state disks Explore backup and recovery strategies—including new tools for hot online backups

     Data Structures and Algorithms in Python is the first mainstream object-oriented book available for the Python data structures course. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++.

    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.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data

    It's used to create and maintain database objects, place data into those objects, query the data, modify the data, and, finally, delete data that is no longer needed. Databases lie at the heart of many, if not most business applications. Chances are very good that if you're involved with software development, you're using SQL to some degree. And if you're using SQL, you should own a good reference or two.Now available in an updated second edition, our very popular "SQL Pocket Guide" is a major help to programmers, database administrators, and everyone who uses SQL in their day-to-day work. The "SQL Pocket Guide" is a concise reference to frequently used SQL statements and commonly used SQL functions. Not just an endless collection of syntax diagrams, this portable guide addresses the language's complexity head on and leads by example. The information in this edition has been updated to reflect the latest versions of the most commonly used SQL variants including: Oracle Database 10g, Release 2 (includingthe free Oracle Database 10g Express Edition (XE))Microsoft SQL Server 2005MySQL 5IBM DB2 8.2PostreSQL 8.1 database

    Although dashboards are potentially powerful, this potential is rarely realized. The greatest display technology in the world won't solve this if you fail to use effective visual design. And if a dashboard fails to tell you precisely what you need to know in an instant, you'll never use it, even if it's filled with cute gauges, meters, and traffic lights. Don't let your investment in dashboard technology go to waste.This book will teach you the visual design skills you need to create dashboards that communicate clearly, rapidly, and compellingly. Information Dashboard Design will explain how to:Avoid the thirteen mistakes common to dashboard design Provide viewers with the information they need quickly and clearly Apply what we now know about visual perception to the visual presentation of information Minimize distractions, cliches, and unnecessary embellishments that create confusion Organize business information to support meaning and usability Create an aesthetically pleasing viewing experience Maintain consistency of design to provide accurate interpretation Optimize the power of dashboard technology by pairing it with visual effectiveness Stephen Few has over 20 years of experience as an IT innovator, consultant, and educator. As Principal of the consultancy Perceptual Edge, Stephen focuses on data visualization for analyzing and communicating quantitative business information. He provides consulting and training services, speaks frequently at conferences, and teaches in the MBA program at the University of California in Berkeley. He is also the author of Show Me the Numbers: Designing Tables and Graphs to Enlighten. Visit his website at www.perceptualedge.com.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    A step-by-step visual journey through the mathematics of neural networks, and making your own using Python and Tensorflow.

    As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way.Expanded from Tyler Akidau's popular blog posts Streaming 101 and Streaming 102, this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You'll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax.You'll explore:How streaming and batch data processing patterns compareThe core principles and concepts behind robust out-of-order data processingHow watermarks track progress and completeness in infinite datasetsHow exactly-once data processing techniques ensure correctnessHow the concepts of streams and tables form the foundations of both batch and streaming data processingThe practical motivations behind a powerful persistent state mechanism, driven by a real-world exampleHow time-varying relations provide a link between stream processing and the world of SQL and relational algebra

    Mastering this art will not only make you the most desired developer in the market, but it will transform the craziest deadline into "Consider it done, Sir".