Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of their organization’s massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you’ll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization. Provides a background in data science fundamentals before moving on to working with relational databases and unstructured data and preparing your data for analysis Details different data visualization techniques that can be used to showcase and summarize your data Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark It’s a big, big data world out there – let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

    This authoritative book scrapes away these bad features to reveal a subset of JavaScript that's more reliable, readable, and maintainable than the language as a whole--a subset you can use to create truly extensible and efficient code.Considered the JavaScript expert by many people in the development community, author Douglas Crockford identifies the abundance of good ideas that make JavaScript an outstanding object-oriented programming language-ideas such as functions, loose typing, dynamic objects, and an expressive object literal notation. Unfortunately, these good ideas are mixed in with bad and downright awful ideas, like a programming model based on global variables.When Java applets failed, JavaScript became the language of the Web by default, making its popularity almost completely independent of its qualities as a programming language. In JavaScript: The Good Parts, Crockford finally digs through the steaming pile of good intentions and blunders to give you a detailed look at all the genuinely elegant parts of JavaScript, including:SyntaxObjectsFunctionsInheritanceArraysRegular expressionsMethodsStyleBeautiful featuresThe real beauty? As you move ahead with the subset of JavaScript that this book presents, you'll also sidestep the need to unlearn all the bad parts. Of course, if you want to find out more about the bad parts and how to use them badly, simply consult any other JavaScript book.With JavaScript: The Good Parts, you'll discover a beautiful, elegant, lightweight and highly expressive language that lets you create effective code, whether you're managing object libraries or just trying to get Ajax to run fast. If you develop sites or applications for the Web, this book is an absolute must.

    Available here:readmeaway.com/download?i=1593279523The Linux Command Line, 2nd Edition: A Complete Introduction PDF by William ShottsRead The Linux Command Line, 2nd Edition: A Complete Introduction PDF from No Starch Press,William ShottsDownload William Shotts’s PDF E-book The Linux Command Line, 2nd Edition: A Complete Introduction

    Based on two popular talks from author Lea Verou--including "CSS3 Secrets: 10 things you may not know about CSS"--this practical guide provides intermediate to advanced CSS developers with more than 40 undocumented techniques and tips for using CSS3 to create better websites.The talks that spawned this book have been top-rated by attendees in every conference they were presented, and praised in industry media such as ."net" magazine.Get information you won't find in any other bookLearn through small, easily digestible chaptersHelps you understand CSS more deeply so you can improve your own solutionsApply Lea's techniques to practically every CSS problem you faceGain tips from a rockstar author who serves as an Invited Expert in W3C's CSS Working Group

    And it’s still short, profusely illustrated…and best of all–fun to read.If you’ve read it before, you’ll rediscover what made Don’t Make Me Think so essential to Web designers and developers around the world. If you’ve never read it, you’ll see why so many people have said it should be required reading for anyone working on Web sites.

    Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

    Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

    Weinberg shows you exactly how to become a more effective consultant. He reveals specific techniques and strategies that really work.Through the use of vividly memorable rules, laws, and principles -- such as The Law of Raspberry Jam, The Potato Chip Principle, and Lessons from the Farm -- the author shows you how to-- price and market your services-- avoid traps and find alternative approaches-- keep ahead of your clients-- create a special "consultant's survival kit"-- trade improvement for perfection-- negotiate in difficult situations-- measure your effectiveness-- be yourselfYou will also find straightforward advice on marketing your services, including how to-- find clients-- get needed exposure-- set just-right fees-- gain trustThe Secrets of Consulting -- techniques, strategies, and first-hand experiences -- all that you'll need to set up, run, and be successful at your own consulting business.

    At under 200 pages it's quick reading too. Makes a great airplane book.

    Albert-László Barabási, the nation’s foremost expert in the new science of networks and author of Bursts, takes us on an intellectual adventure to prove that social networks, corporations, and living organisms are more similar than previously thought. Grasping a full understanding of network science will someday allow us to design blue-chip businesses, stop the outbreak of deadly diseases, and influence the exchange of ideas and information. Just as James Gleick and the Erdos–Rényi model brought the discovery of chaos theory to the general public, Linked tells the story of the true science of the future and of experiments in statistical mechanics on the internet, all vital parts of what would eventually be called the Barabási–Albert model.

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started?Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others.You'll learn how to: Identify the metrics you need to measure Run experiments and A/B tests Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes

    Infrastructure engineers use a software version of this “chaos monkey” to test online services’ robustness—their ability to survive random failure and correct mistakes before they actually occur. Tech entrepreneurs are society’s chaos monkeys, disruptors testing and transforming every aspect of our lives, from transportation (Uber) and lodging (AirBnB) to television (Netflix) and dating (Tinder). One of Silicon Valley’s most audacious chaos monkeys is Antonio García Martínez.After stints on Wall Street and as CEO of his own startup, García Martínez joined Facebook’s nascent advertising team, turning its users’ data into profit for COO Sheryl Sandberg and chairman and CEO Mark “Zuck” Zuckerberg. Forced out in the wake of an internal product war over the future of the company’s monetization strategy, García Martínez eventually landed at rival Twitter. He also fathered two children with a woman he barely knew, committed lewd acts and brewed illegal beer on the Facebook campus (accidentally flooding Zuckerberg's desk), lived on a sailboat, raced sport cars on the 101, and enthusiastically pursued the life of an overpaid Silicon Valley wastrel.Now, this gleeful contrarian unravels the chaotic evolution of social media and online marketing and reveals how it is invading our lives and shaping our future. Weighing in on everything from startups and credit derivatives to Big Brother and data tracking, social media monetization and digital “privacy,” García Martínez shares his scathing observations and outrageous antics, taking us on a humorous, subversive tour of the fascinatingly insular tech industry. Chaos Monkeys lays bare the hijinks, trade secrets, and power plays of the visionaries, grunts, sociopaths, opportunists, accidental tourists, and money cowboys who are revolutionizing our world. The question is, will we survive?

    In its sweeping survey of the history of Internet search technologies, its gossip about and analysis of Google, and its speculation on the larger cultural implications of a Web-connected world, it will likely receive attention from a variety of businesspeople, technology futurists, journalists, and interested observers of mid-2000s zeitgeist. This ambitious book comes with a strong pedigree. Author John Battelle was a founder of The Industry Standard and then one of the original editors of Wired, two magazines which helped shape our early perceptions of the wild world of the Internet. Battelle clearly drew from his experience and contacts in writing The Search. In addition to the sure-handed historical perspective and easy familiarity with such dot-com stalwarts as AltaVista, Lycos, and Excite, he speckles his narrative with conversational asides from a cast of fascinating characters, such Google's founders, Larry Page and Sergey Brin; Yahoo's, Jerry Yang and David Filo; key executives at Microsoft and different VC firms on the famed Sandhill road; and numerous other insiders, particularly at the company which currently sits atop the search world, Google. The Search is not exactly the corporate history of Google. At the book's outset, Battelle specifically indicates his desire to understand what he calls the cultural anthropology of search, and to analyze search engines' current role as the "database of our intentions"--the repository of humanity's curiosity, exploration, and expressed desires. Interesting though that beginning is, though, Battelle's story really picks up speed when he starts dishing inside scoop on the darling business story of the decade, Google. To Battelle's credit, though, he doesn't stop just with historical retrospective: the final part of his book focuses on the potential future directions of Google and its products' development. In what Battelle himself acknowledges might just be a "digital fantasy train", he describes the possibility that Google will become the centralizing platform for our entire lives and quotes one early employee on the weightiness of Google's potential impact: "Sometimes I feel like I am on a bridge, twenty thousand feet up in the air. If I look down I'm afraid I'll fall. I don't feel like I can think about all the implications." Some will shrug at such words; after all, similar hype has accompanied other technologies and other companies before. Many others, though, will search Battelle's story for meaning--and fast. --Peter Han

    By “reverse engineering the fastest growing company in the history of the world,” author Jeff Jarvis, proprietor of Buzzmachine.com, one of the Web’s most widely respected media blogs, offers indispensible strategies for solving the toughest new problems facing businesses today. With a new afterword from the author, What Would Google Do? is the business book that every leader or potential leader in every industry must read.