Book picks similar to
Big Data Now: 2012 Edition by O'Reilly Media Inc.


big-data
non-fiction
information-technology
technology

The LogStash Book


James Turnbull - 2013
    We're going to do that by introducing you to Example.com, where you're going to start a new job as one of its SysAdmins. The first project you'll be in charge of is developing its new log management solution. We'll teach you how to:* Install and deploy LogStash.* Ship events from a LogStash Shipper to a central LogStash server.* Filter incoming events using a variety of techniques.* Output those events to a selection of useful destinations.* Use LogStash's Web interface and alternative interfaces like Kibana.* Scale out your LogStash implementation as your environment grows.* Quickly and easily extend LogStash to deliver additional functionality you might need.By the end of the book you should have a functional and effective log management solution that you can deploy into your own environment.

CSS and Documents


Eric A. Meyer - 2012
    

Learn Java in One Day and Learn It Well: Java for Beginners with Hands-on Project


Jamie Chan - 2016
    Learn Java Programming Fast with a unique Hands-On Project. Book 4 of the Learn Coding Fast Series. Covers Java 8. Have you always wanted to learn computer programming but are afraid it'll be too difficult for you? Or perhaps you know other programming languages but are interested in learning the Java language fast? This book is for you. You no longer have to waste your time and money trying to learn Java from boring books that are 600 pages long, expensive online courses or complicated Java tutorials that just leave you more confused and frustrated. What this book offers... Java for Beginners Complex concepts are broken down into simple steps to ensure that you can easily master the Java language even if you have never coded before. Carefully Chosen Java Examples Examples are carefully chosen to illustrate all concepts. In addition, the output for all examples are provided immediately so you do not have to wait till you have access to your computer to test the examples. Careful selection of topics Topics are carefully selected to give you a broad exposure to Java, while not overwhelming you with information overload. These topics include object-oriented programming concepts, error handling techniques, file handling techniques and more. In addition, new features in Java (such as lambda expressions and default methods etc) are also covered so that you are always up to date with the latest advancement in the Java language. Learn The Java Programming Language Fast Concepts are presented in a "to-the-point" style to cater to the busy individual. You no longer have to endure boring and lengthy Java textbooks that simply puts you to sleep. With this book, you can learn Java fast and start coding immediately. How is this book different... The best way to learn Java is by doing. This book includes a unique project at the end of the book that requires the application of all the concepts taught previously. Working through the project will not only give you an immense sense of achievement, it’ll also help you retain the knowledge and master the language. Are you ready to dip your toes into the exciting world of Java coding? This book is for you. Click the BUY button and download it now. What you'll learn: Introduction to Java - What is Java? - What software do you need to code Java programs? - How to install and run JDK and Netbeans? Data types and Operators - What are the eight primitive types in Java? - What are arrays and lists? - How to format Java strings - What is a primitive type vs reference type? - What are the common Java operators? Object Oriented Programming - What is object oriented programming? - How to write your own classes - What are fields, methods and constructors? - What is encapsulation, inheritance and polymorphism? - What is an abstract class and interface? Controlling the Flow of a Program - What are condition statements? - How to use control flow statements in Java - How to handle errors and exceptions - How to throw your own exception

Building Cloud Apps with Microsoft Azure: Best Practices for DevOps, Data Storage, High Availability, and More (Developer Reference)


Scott Guthrie - 2014
    The patterns apply to the development process as well as to architecture and coding practices. The content is based on a presentation developed by Scott Guthrie and delivered by him at the Norwegian Developers Conference (NDC) in June of 2013 (part 1, part 2), and at Microsoft Tech Ed Australia in September 2013 (part 1, part 2). Many others updated and augmented the content while transitioning it from video to written form. Who should read this book Developers who are curious about developing for the cloud, are considering a move to the cloud, or are new to cloud development will find here a concise overview of the most important concepts and practices they need to know. The concepts are illustrated with concrete examples, and each chapter includes links to other resources that provide more in-depth information. The examples and the links to additional resources are for Microsoft frameworks and services, but the principles illustrated apply to other web development frameworks and cloud environments as well. Developers who are already developing for the cloud may find ideas here that will help make them more successful. Each chapter in the series can be read independently, so you can pick and choose topics that you're interested in. Anyone who watched Scott Guthrie's "Building Real World Cloud Apps with Windows Azure" presentation and wants more details and updated information will find that here. Assumptions This ebook expects that you have experience developing web applications by using Visual Studio and ASP.NET. Familiarity with C# would be helpful in places.

Storytelling with Data: A Data Visualization Guide for Business Professionals


Cole Nussbaumer Knaflic - 2015
    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!

The Hundred-Page Machine Learning Book


Andriy Burkov - 2019
    During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.

Data Analysis with Open Source Tools: A Hands-On Guide for Programmers and Data Scientists


Philipp K. Janert - 2010
    With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora

Prediction Machines: The Simple Economics of Artificial Intelligence


Ajay Agrawal - 2018
    But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.When AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity--operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete. Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

Introducing Windows 8.1 for It Professionals


Ed Bott - 2013
    It is offered for sale in print format as a convenience.Get a head start evaluating Windows 8.1 - with early technical insights from award-winning journalist and Windows expert Ed Bott. Based on the Windows 8.1 Preview release, this guide introduces new features and capabilities, with scenario-based advice on how Windows 8.1 can meet the needs of your business. Get the high-level overview you need to begin preparing your deployment now.Preview new features and enhancements, including:How features compare to Windows 7 and Windows XP The Windows 8.1 user experience Deployment Security features Internet Explorer 11 Delivering Windows apps Recovery options Networking and remote access Managing mobile devices Virtualization Windows RT 8.1

Training Kit (Exam 70-461): Querying Microsoft SQL Server 2012


Itzik Ben-Gan - 2012
    Work at your own pace through a series of lessons and practical exercises, and then assess your skills with practice tests on CD—featuring multiple, customizable testing options.Maximize your performance on the exam by learning how to:Create database objectsWork with dataModify dataTroubleshoot and optimize queriesYou also get an exam discount voucher—making this book an exceptional value and a great career investment.

Architecting for the AWS Cloud: Best Practices (AWS Whitepaper)


Amazon We Services - 2016
    It discusses cloud concepts and highlights various design patterns and best practices. This documentation is offered for free here as a Kindle book, or you can read it in PDF format at https://aws.amazon.com/whitepapers/.

The Cathedral & the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary


Eric S. Raymond - 1999
    According to the August Forrester Report, 56 percent of IT managers interviewed at Global 2,500 companies are already using some type of open source software in their infrastructure and another 6 percent will install it in the next two years. This revolutionary model for collaborative software development is being embraced and studied by many of the biggest players in the high-tech industry, from Sun Microsystems to IBM to Intel.The Cathedral & the Bazaar is a must for anyone who cares about the future of the computer industry or the dynamics of the information economy. Already, billions of dollars have been made and lost based on the ideas in this book. Its conclusions will be studied, debated, and implemented for years to come. According to Bob Young, "This is Eric Raymond's great contribution to the success of the open source revolution, to the adoption of Linux-based operating systems, and to the success of open source users and the companies that supply them."The interest in open source software development has grown enormously in the past year. This revised and expanded paperback edition includes new material on open source developments in 1999 and 2000. Raymond's clear and effective writing style accurately describing the benefits of open source software has been key to its success. With major vendors creating acceptance for open source within companies, independent vendors will become the open source story in 2001.

Hands-On Machine Learning with Scikit-Learn and TensorFlow


Aurélien Géron - 2017
    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

Introducing Windows Server 2012


Mitch Tulloch - 2012
    This practical introduction illuminates new features and capabilities, with scenarios demonstrating how the platform can meet the needs of your business.Based on beta software, this book provides the early, high-level information you need to begin preparing now for deployment and management. Topics include:Virtualization and cloud solutions Availability Provisioning and storage management Security and scalability Infrastructure options Server administration

Data Smart: Using Data Science to Transform Information into Insight


John W. Foreman - 2013
    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.