We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that.This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples.By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to:- How to measure your own level of uncertainty in a conclusion or belief- Calculate Bayes theorem and understand what it's useful for- Find the posterior, likelihood, and prior to check the accuracy of your conclusions- Calculate distributions to see the range of your data- Compare hypotheses and draw reliable conclusions from themNext time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.

    No longer. A new generation of tools and massive amounts of available data make it easy for anyone to create visualizations that communicate ideas far more effectively than generic spreadsheet charts ever could.What’s more, building good charts is quickly becoming a need-to-have skill for managers. If you’re not doing it, other managers are, and they’re getting noticed for it and getting credit for contributing to your company’s success.In Good Charts, dataviz maven Scott Berinato provides an essential guide to how visualization works and how to use this new language to impress and persuade. Dataviz today is where spreadsheets and word processors were in the early 1980s—on the cusp of changing how we work. Berinato lays out a system for thinking visually and building better charts through a process of talking, sketching, and prototyping.This book is much more than a set of static rules for making visualizations. It taps into both well-established and cutting-edge research in visual perception and neuroscience, as well as the emerging field of visualization science, to explore why good charts (and bad ones) create “feelings behind our eyes.” Along the way, Berinato also includes many engaging vignettes of dataviz pros, illustrating the ideas in practice.Good Charts will help you turn plain, uninspiring charts that merely present information into smart, effective visualizations that powerfully convey ideas.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    The author was—at first.When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind.Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold.This book will help you understand:• Why big data is important to you and your organization• What technology you need to manage it• How big data could change your job, your company, and your industry• How to hire, rent, or develop the kinds of people who make big data work• The key success factors in implementing any big data project• How big data is leading to a new approach to managing analyticsWith dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.

    This title identifies the twelve fundamental design principles for building killer apps. It illustrates these principles with classic stories from history and examples from a range of industries that have successfully developed killer apps.

    Marine Corps has been a paragon of world-class leadership, excelling in the areas of motivation, training, and management. Semper Fi -- which since its hardcover publication has become a best-selling, business leadership classic -- shows readers how to adapt these proven practices for their own organizations. Semper Fi goes behind the scenes to pinpoint what works for the USMC, showing readers how to create a training and management culture that brings out the best in all their employees. The book gives readers tough, practical tips for: * inspiring individual initiative * rewarding hard work * encouraging loyalty * working with limited resources * dealing with change * "leading the troops"" at every level of the organization. "This is not," according to Dan Rather, "one of those mumbo-jumbo, pseudo-philosophical books on leadership. Semper Fi is a book you will actually USE, read, and refer to again and again."

    You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples--ready for immediate application to your next graph or presentation.Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to:Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data--Storytelling with Data will give you the skills and power to tell it!

    Founded in the regulated and stagnant Indian economy of the late 1980s, offering a credit rating service that had no takers, and without any real assets or capital, CRISIL seemed destined to fail. Instead, it became one of India’s most respected companies, redefining its vision from being India-focused to playing a quiet but critical role in global markets. This is a story of razor-sharp analytics, unshakeable values and sheer grit. It is also a story of leaders with very different styles, who brought it all together over a quarter of a century. A narrative that, above all, shows that doing well can go hand in hand with doing what is right.

    If you’re looking for the original book, search this link http://amzn.to/2uzu0Xl) Charles Bukowski was a popular author and poet, but his rise to fame was difficult. He was a drunk and he was crude. He was middle-aged by the time someone published one of his novels. However, fame did not change Bukowski. He continued to live the drunken life of a loser. His writing was popular because it was honest. In the end, Charles Bukowski became famous because he didn’t care what other people thought of him.Our culture defines success by how much stuff we have. The more we have, the better life we must lead. The problem is that society tells us what we need by reminding us what we lack. We become dissatisfied with our current situation, and strive to get whatever is bigger and better. While this is a good strategy if you’re a business, as a consumer it causes us to never be content with what we have.Advertisements tell us to give a fuck about everything, because it’s good for their businesses. The author urges us to give a fuck about only the important things in life... Read more.... This is a ZERO-RISK investment. Should you find this book unworthy of the original coffee price of $2.99, get a REFUND within 7 days! The Time for Thinking is Over! Time for Action! Scroll Up Now and Click on the “Buy now with 1-Click” Button to Download your Copy Right Away! (Disclaimer: This is NOT the original book. If you’re looking for the original book, search this link: http://amzn.to/2uzu0Xl

    This book is streamlined to include only core certification information, and is presented for ease of last-minute studying. Main objectives of the exam are covered concisely with key concepts highlighted. The CISSP certification is the most prestigious, globally-recognized, vendor neutral exam for information security professionals. Over 100,000 professionals are certified worldwide, with many more joining their ranks. This new third edition is aligned to cover all of the material in the most current version of the exam’s Common Body of Knowledge. All domains are covered as completely and concisely as possible, giving users the best possible chance of acing the exam. Completely updated for the most current version of the exam’s Common Body of Knowledge Provides the only guide you need for last-minute studying Answers the toughest questions and highlights core topics Streamlined for maximum efficiency of study, making it ideal for professionals updating their certification or for those taking the test for the first time

    When former Goldman Sachs colleagues Stuart Sternberg and Matthew Silverman assumed control of the Tampa Bay Devil Rays in 2005, it looked as if they were buying the baseball equivalent of a penny stock. But the incoming regime came armed with a master plan: to leverage their skill at trading, valuation, and management to build a model twenty-first-century franchise that could compete with their bigger, stronger, richer rivals—and prevail.Together with “boy genius” general manager Andrew Friedman, the new Rays owners jettisoned the old ways of doing things, substituting their own innovative ideas about employee development, marketing and public relations, and personnel management. They exorcized the “devil” from the team’s nickname, developed metrics that let them take advantage of undervalued aspects of the game, like defense, and hired a forward-thinking field manager as dedicated to unconventional strategy as they were. By quantifying the game’s intangibles—that extra 2% that separates a winning organization from a losing one—they were able to deliver to Tampa Bay something that Billy Beane’s “Moneyball” had never brought to Oakland: an American League pennant.A book about what happens when you apply your business skills to your life’s passion, The Extra 2% is an informative and entertaining case study for any organization that wants to go from worst to first.

    Information is provided on the fundamental concepts of table and graph design, the numbers and knowledge most suitable for display in a graphic form, the best tabular means to communicate certain ideas, and the component-level aspects of design. Analysts, technicians, and managers will appreciate the solid theory behind this outline for ensuring that tables and graphs present quantitative business information in a truthful, attractive format that facilitates better decision making.

    Yet these beliefs are largely based on guesswork and incomplete data and lead to costly errors in judgment. Now, internationally renowned innovation expert Clayton M. Christensen and his research partners Scott D. Anthony and Erik A. Roth present a groundbreaking framework for predicting outcomes in the evolution of any industry. Based on proven theories outlined in Christensen's landmark books The Innovator's Dilemma and The Innovator's Solution, Seeing What's Next offers a practical, three-part model that helps decision-makers spot the signals of industry change, determine the outcome of competitive battles, and assess whether a firm's actions will ensure or threaten future success. Through in-depth case studies of industries from aviation to health care, the authors illustrate the predictive power of innovation theory in action.

    Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters. Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Take advantage of HBase, Hadoop's database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject. "Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk." -- Doug Cutting, Hadoop Founder, Yahoo!