R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you'll need to accomplish 80 percent of modern data tasks. Lander's self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You'll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you'll construct several complete models, both linear and nonlinear, and use some data mining techniques. By the time you're done, you won't just know how to write R programs, you'll be ready to tackle the statistical problems you care about most. COVERAGE INCLUDES - Exploring R, RStudio, and R packages - Using R for math: variable types, vectors, calling functions, and more - Exploiting data structures, including data.frames, matrices, and lists - Creating attractive, intuitive statistical graphics - Writing user-defined functions - Controlling program flow with if, ifelse, and complex checks - Improving program efficiency with group manipulations - Combining and reshaping multiple datasets - Manipulating strings using R's facilities and regular expressions - Creating normal, binomial, and Poisson probability distributions - Programming basic statistics: mean, standard deviation, and t-tests - Building linear, generalized linear, and nonlinear models - Assessing the quality of models and variable selection - Preventing overfitting, using the Elastic Net and Bayesian methods - Analyzing univariate and multivariate time series data - Grouping data via K-means and hierarchical clustering - Preparing reports, slideshows, and web pages with knitr - Building reusable R packages with devtools and Rcpp - Getting involved with the R global community

    The title says it is the hard way to learn to writecode but it’s actually not. It’s the “hard” way only in that it’s the way people used to teach things. In this book youwill do something incredibly simple that all programmers actually do to learn a language: 1. Go through each exercise. 2. Type in each sample exactly. 3. Make it run.That’s it. This will be very difficult at first, but stick with it. If you go through this book, and do each exercise for1-2 hours a night, then you’ll have a good foundation for moving on to another book. You might not really learn“programming” from this book, but you will learn the foundation skills you need to start learning the language.This book’s job is to teach you the three most basic essential skills that a beginning programmer needs to know:Reading And Writing, Attention To Detail, Spotting Differences.

    Although companies of every kind have successfully implemented his original design ideas across hundreds of systems, these insights have never before appeared in print.Based on first principles in software engineering and a comprehensive set of matching tools and techniques, Löwy's methodology integrates system design and project design. First, he describes the primary area where many software architects fail and shows how to decompose a system into smaller building blocks or services, based on volatility. Next, he shows how to flow an effective project design from the system design; how to accurately calculate the project duration, cost, and risk; and how to devise multiple execution options.The method and principles in Righting Software apply regardless of your project and company size, technology, platform, or industry. Löwy starts the reader on a journey that addresses the critical challenges of software development today by righting software systems and projects as well as careers-and possibly the software industry as a whole. Software professionals, architects, project leads, or managers at any stage of their career will benefit greatly from this book, which provides guidance and knowledge that would otherwise take decades and many projects to acquire. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

    From entertainment to politics, from technology to advertising and from science to the business world, understanding and using data is now one of the most transferable and transferable skills out there. Learning how to work with data may seem intimidating or difficult but with Confident Data Skills you will be able to master the fundamentals and supercharge your professional abilities. This essential book covers data mining, preparing data, analysing data, communicating data, financial modelling, visualizing insights and presenting data through film making and dynamic simulations.In-depth international case studies from a wide range of organizations, including Netflix, LinkedIn, Goodreads, Deep Blue, Alpha Go and Mike's Hard Lemonade Co. show successful data techniques in practice and inspire you to turn knowledge into innovation. Confident Data Skills also provides insightful guidance on how you can use data skills to enhance your employability and improve how your industry or company works through your data skills. Expert author and instructor, Kirill Eremenko, is committed to making the complex simple and inspiring you to have the confidence to develop an understanding, adeptness and love of data.

    Scientists have marveled at the beauty and elegance of his analysis, while ordinary programmers have successfully applied his "cookbook" solutions to their day-to-day problems. All have admired Knuth for the breadth, clarity, accuracy, and good humor found in his books. "I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me I have pored over them in cars, restaurants, at work, at home... and even at a Little League game when my son wasn't in the line-up.""--"Charles Long Primarily written as a reference, some people have nevertheless found it possible and interesting to read each volume from beginning to end. A programmer in China even compared the experience to reading a poem. "If you think you're a really good programmer... read Knuth's] "Art of Computer Programming.".. You should definitely send me a resume if you can read the whole thing.""--"Bill Gates Whatever your background, if you need to do any serious computer programming, you will find your own good reason to make each volume in this series a readily accessible part of your scholarly or professional library. "It's always a pleasure when a problem is hard enough that you have to get the Knuths off the shelf. I find that merely opening one has a very useful terrorizing effect on computers.""--"Jonathan LaventholIn describing the new fourth volume, one reviewer listed the qualities that distinguish all of Knuth's work. In sum: ] "detailed coverage of the basics, illustrated with well-chosen examples; occasional forays into more esoteric topics and problems at the frontiers of research; impeccable writing peppered with occasional bits of humor; extensive collections of exercises, all with solutions or helpful hints; a careful attention to history; implementations of many of the algorithms in his classic step-by-step form."--Frank RuskeyThese four books comprise what easily could be the most important set of information on any serious programmer's bookshelf.

     If you have ever found yourself lost halfway through other introductory materials on this topic, this is the book for you. If you don't understand set terminology such as vectors, hyperplanes, and centroids, then this is also the book for you. This starter course isn't a picture story book but does include many visual examples that break algorithms down into a digestible and practical format. As a starter course, this book connects the dots and offers the crash course I wish I had when I first started. The kind of guide I wish had before I started taking on introductory courses that presume you’re two days away from an advanced mathematics exam. That’s why this introductory course doesn’t go further on the subject than other introductory books, but rather, goes a step back. A half-step back in order to help everyone make his or her first strides in machine learning and is an ideal study companion for the visual learner. In this step-by-step guide you will learn: - How to download free datasets - What tools and software packages you need - Data scrubbing techniques, including one-hot encoding, binning and dealing with missing data - Preparing data for analysis, including k-fold Validation - Regression analysis to create trend lines - Clustering, including k-means and k-nearest Neighbors - Naive Bayes Classifier to predict new classes - Anomaly detection and SVM algorithms to combat anomalies and outliers - The basics of Neural Networks - Bias/Variance to improve your machine learning model - Decision Trees to decode classification Please feel welcome to join this starter course by buying a copy, or sending a free sample to your preferred device.

    Cloud computing is rapidly transitioning from a niche technology embraced by startups and tech-forward companies to the foundation upon which enterprise systems build their future. In order to compete in today’s marketplace, organizations large and small are embracing cloud architectures and practices.

    It is a conversational book that feels easy and informative. This short and lucid book covers everything important, with concrete examples, and invites the reader to join this field. The chapters in the book are organized for a typical one-semester course. The book contains case-lets from real-world stories at the beginning of every chapter. There is a running case study across the chapters as exercises. This book is designed to provide a student with the intuition behind this evolving area, along with a solid toolset of the major data mining techniques and platforms. Students across a variety of academic disciplines, including business, computer science, statistics, engineering, and others are attracted to the idea of discovering new insights and ideas from data. This book can also be gainfully used by executives, managers, analysts, professors, doctors, accountants, and other professionals to learn how to make sense of the data coming their way. This is a lucid flowing book that one can finish in one sitting, or can return to it again and again for insights and techniques. Table of Contents Chapter 1: Wholeness of Business Intelligence and Data Mining Chapter 2: Business Intelligence Concepts & Applications Chapter 3: Data Warehousing Chapter 4: Data Mining Chapter 5: Decision Trees Chapter 6: Regression Models Chapter 7: Artificial Neural Networks Chapter 8: Cluster Analysis Chapter 9: Association Rule Mining Chapter 10: Text Mining Chapter 11: Web Mining Chapter 12: Big Data Chapter 13: Data Modeling Primer Appendix: Data Mining Tutorial using Weka

    But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

    We can all learn from these strategies. In this detailed analysis of IoT and Amazon's and other leading companies approach to it, John Rossman guides readers with practical insights and recommendations into the strategies and mindset transforming business and society. "John has laid out a blueprint not only for an enterprise wanting to understand how sensors embedded in their business can innovate old ways of working while also providing an excellent path for individuals wanting to start their own IoT business. The book is not only a reference tool but also paints a story around innovation and customer centricity to challenge the reader to think differently in solving problems." Eric Martinez -- Founder of Modjoul, former EVP AIG and Safeco Insurance The Amazon Way on IoT explains how the combination of sensors, cloud computing and machine learning can be used to improve customer experiences, drive operational improvements and build new business models. Rossman offers: - Guidance through the maze of emerging technologies, customer experiences, and business models, to arrive at a recipe just right for your organization - Key methods to success from Amazon’s master playbook such as creating seamless customer experiences, process improvement and new business models and utilizing tools such as sensors, machine learning and cloud computing - Approaches to help you tackle the technology, business and internal challenges in innovating with the internet of things. Renowned Harvard business professor Michael Porter describes the IoT as the backbone for a third-wave of technology-led innovation and digital disruption. The Amazon Way on IoT is for business people who want to learn cases, key concepts, technologies and tools to help develop, explain and execute their own IoT approach. As a leader at Amazon who held a front-row seat during its formative years, Rossman understands the iconic company better than most. From the launch of Amazon’s third-party seller program to its foray into enterprise services, he witnessed it all – the amazing successes, the little-known failures, and the experiments with outcomes still to be determined. Rossman once again examines the heart of Amazon.com’s secret to success, along with other leading companies. He incorporates an extensive focus on sophisticated IoT technologies and strategies related to Amazon’s rise: tens of millions of items in stock, the company’s technological prowess, and the many customer service innovations such as “one-click.” “This is an excellent book. And a very important book. It evokes both business thought and technical thought, which is rare.” -- Larry Hughes, former head of Amazon cyber security

    At many companies, being first with a concept and first to market are critical just to survive. In The Art of Innovation, Tom Kelley, general manager of the Silicon Valley based design firm IDEO, takes readers behind the scenes of this wildly imaginative and energized company to reveal the strategies and secrets it uses to turn out hit after hit.IDEO doesn't buy into the myth of the lone genius working away in isolation, waiting for great ideas to strike. Kelley believes everyone can be creative, and the goal at his firm is to tap into that wellspring of creativity in order to make innovation a way of life. How does it do that? IDEO fosters an atmosphere conducive to freely expressing ideas, breaking the rules, and freeing people to design their own work environments. IDEO's focus on teamwork generates countless breakthroughs, fueled by the constant give-and-take among people ready to share ideas and reap the benefits of the group process. IDEO has created an intense, quick-turnaround, brainstorm-and-build process dubbed "the Deep Dive."In entertaining anecdotes, Kelley illustrates some of his firm's own successes (and joyful failures), as well as pioneering efforts at other leading companies. The book reveals how teams research and immerse themselves in every possible aspect of a new product or service, examining it from the perspective of clients, consumers, and other critical audiences.Kelley takes the reader through the IDEO problem-solving method:> Carefully observing the behavior or "anthropology" of the people who will be using a product or service> Brainstorming with high-energy sessions focused on tangible results> Quickly prototyping ideas and designs at every step of the way> Cross-pollinating to find solutions from other fields> Taking risks, and failing your way to success> Building a "Greenhouse" for innovationIDEO has won more awards in the last ten years than any other firm of its kind, and a full half-hour Nightline presentation of its creative process received one of the show's highest ratings. The Art of Innovation will provide business leaders with the insights and tools they need to make their companies the leading-edge, top-rated stars of their industries.From the Hardcover edition.

    Now, for the first time, there's an accessible guide to the basics of DDD: What it is, what problems it solves, how it works, and how to quickly gain value from it. Concise, readable, and actionable, Domain-Driven Design Distilled never buries you in detail-it focuses on what you need to know to get results. Vaughn Vernon, author of the best-selling Implementing Domain-Driven Design, draws on his twenty years of experience applying DDD principles to real-world situations. He is uniquely well-qualified to demystify its complexities, illuminate its subtleties, and help you solve the problems you might encounter. Vernon guides you through each core DDD technique for building better software. You'll learn how to segregate domain models using the powerful Bounded Contexts pattern, to develop a Ubiquitous Language within an explicitly bounded context, and to help domain experts and developers work together to create that language. Vernon shows how to use Subdomains to handle legacy systems and to integrate multiple Bounded Contexts to define both team relationships and technical mechanisms. Domain-Driven Design Distilled brings DDD to life. Whether you're a developer, architect, analyst, consultant, or customer, Vernon helps you truly understand it so you can benefit from its remarkable power. Coverage includes What DDD can do for you and your organization-and why it's so important The cornerstones of strategic design with DDD: Bounded Contexts and Ubiquitous Language Strategic design with Subdomains Context Mapping: helping teams work together and integrate software more strategically Tactical design with Aggregates and Domain Events Using project acceleration and management tools to establish and maintain team cadence

    Visible Ops is comprised of four prescriptive and self-fueling steps that take an organization from any starting point to a continually improving process. MAKING ITIL ACTIONABLE Although the Information Technology Infrastructure Library (ITIL) provides a wealth of best practices, it lacks prescriptive guidance: What do you implement first, and how do you do it? Moreover, the ITIL books remain relatively expensive to distribute. Other information, publicly available from a variety of sources, is too general and vague to effectively aid organizations that need to start or enhance process improvement efforts. The Visible Ops booklet provides a prescriptive roadmap for organizations beginning or continuing their IT process improvement journey. WHY DO WE NEED VISIBLE OPS? The Visible Ops methodology was developed because there was not a satisfactory answer to the question: "I believe in the need for IT process improvement, but where do I start?" Since 2000, Gene Kim and Kevin Behr have met with hundreds of IT organizations and identified eight high-performing IT organizations with the highest service levels, best security, and best efficiencies. For years, they studied these high-performing organizations to figure out the secrets to their success. Visible Ops codifies how these organizations achieved their transformation from good to great, showing how interested organizations can replicate the key processes of these high-performing organizations in just four steps: 1. Stabilize Patient, Modify First Response - Almost 80% of outages are self-inflicted. The first step is to control risky changes and reduce MTTR by addressing how changes are managed and how problems are resolved. 2. Catch and Release, Find Fragile Artifacts - Often, infrastructure exists that cannot be repeatedly replicated. In this step, we inventory assets, configurations and services, to identify those with the lowest change success rates, highest MTTR and highest business downtime costs. 3. Establish Repeatable Build Library - The highest return on investment is implementing effective release management processes. This step creates repeatable builds for the most critical assets and services, to make it "cheaper to rebuild than to repair." 4. Enable Continuous Improvement - The previous steps have progressively built a closed-loop between the Release, Control and Resolution processes. This step implements metrics to allow continuous improvement of all of these process areas, to best ensure that business objectives are met.

    However, many groups have floundered in their practice-oriented adoptions. Why? Because without a deeper understanding of the thinking tools and profound organizational redesign needed, it is as though casting seeds on to an infertile field. Now, drawing on their long experience leading and guiding large-scale lean and agile adoptions for large, multisite, and offshore product development, and drawing on the best research for great team-based agile organizations, internationally recognized consultant and best-selling author Craig Larman and former leader of the agile transformation at Nokia Networks Bas Vodde share the key thinking and organizational tools needed to plant the seeds of product development success in a fertile lean and agile enterprise. Coverage includes Lean thinking and development combined with agile practices and methods Systems thinking Queuing theory and large-scale development processes Moving from single-function and component teams to stable cross-functional cross-component Scrum feature teams with end-to-end responsibility for features Organizational redesign to a lean and agile enterprise that delivers value fast Large-scale Scrum for multi-hundred-person product groups In a competitive environment that demands ever-faster cycle times and greater innovation, applied lean thinking and agile principles are becoming an urgent priority. Scaling Lean & Agile Development will help leaders create the foundation for their lean enterprise-and deliver on the significant benefits of agility. In addition to the foundation tools in this text, see the companion book Practices for Scaling Lean & Agile Development: Large, Multisite, and Offshore Product Development with Large-Scale Scrum for complementary action tools.

    A simple web search picks out a handful of relevant needles from the world's biggest haystack: the billions of pages on the World Wide Web. Uploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers; and we use digital signatures to verify the identity of the websites we visit. How do our computers perform these tasks with such ease? This is the first book to answer that question in language anyone can understand, revealing the extraordinary ideas that power our PCs, laptops, and smartphones. Using vivid examples, John MacCormick explains the fundamental "tricks" behind nine types of computer algorithms, including artificial intelligence (where we learn about the "nearest neighbor trick" and "twenty questions trick"), Google's famous PageRank algorithm (which uses the "random surfer trick"), data compression, error correction, and much more. These revolutionary algorithms have changed our world: this book unlocks their secrets, and lays bare the incredible ideas that our computers use every day.