The result is a stunning achievement in graphics education. Through the ideas and software in this book, you will learn to design and employ a full-featured rendering system for creating stunning imagery.This new edition greatly refines its best-selling predecessor by streamlining all obsolete code as well as adding sections on parallel rendering and system design; animating transformations; multispectral rendering; realistic lens systems; blue noise and adaptive sampling patterns and reconstruction; measured BRDFs; and instant global illumination, as well as subsurface and multiple-scattering integrators.These updates reflect the current state-of-the-art technology, and along with the lucid pairing of text and code, ensure the book's leading position as a reference text for those working with images, whether it is for film, video, photography, digital design, visualization, or gaming.

    These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion. These are just basic examples of the growth of Web intelligence, as increasingly sophisticated algorithms operate on the vast and growing amount of data on the Web, sifting, selecting, comparing, aggregating, correcting; following simple but powerful rules to decide what matters. While original optimism for Artificial Intelligence declined, this new kind of machine intelligence is emerging as the Web grows ever larger and more interconnected.Gautam Shroff takes us on a journey through the computer science of search, natural language, text mining, machine learning, swarm computing, and semantic reasoning, from Watson to self-driving cars. This machine intelligence may even mimic at a basic level what happens in the brain.

    You'll get quick, easy-to-follow advice on modern practices: which to use, and when they should be applied. This book avoids current fashion trends and marketing hype; instead, readers find page after page of solid advice, all tried and tested in the real world.Aimed at beginning to intermediate programmers, Ship It! will show you:Which tools help, and which don't How to keep a project moving Approaches to scheduling that work How to build developers as well as product What's normal on a project, and what's not How to manage managers, end-users and sponsors Danger signs and how to fix them Few of the ideas presented here are controversial or extreme; most experienced programmers will agree that this stuff works. Yet 50 to 70 percent of all project teams in the U.S. aren't able to use even these simple, well-accepted practices effectively. This book will help you get started.Ship It! begins by introducing the common technical infrastructure that every project needs to get the job done. Readers can choose from a variety of recommended technologies according to their skills and budgets. The next sections outline the necessary steps to get software out the door reliably, using well-accepted, easy-to-adopt, best-of-breed practices that really work.Finally, and most importantly, Ship It! presents common problems that teams face, then offers real-world advice on how to solve them.

    In Dataclysm, Christian Rudder uses it to show us who we truly are.   For centuries, we’ve relied on polling or small-scale lab experiments to study human behavior. Today, a new approach is possible. As we live more of our lives online, researchers can finally observe us directly, in vast numbers, and without filters. Data scientists have become the new demographers.   In this daring and original book, Rudder explains how Facebook "likes" can predict, with surprising accuracy, a person’s sexual orientation and even intelligence; how attractive women receive exponentially more interview requests; and why you must have haters to be hot. He charts the rise and fall of America’s most reviled word through Google Search and examines the new dynamics of collaborative rage on Twitter. He shows how people express themselves, both privately and publicly. What is the least Asian thing you can say? Do people bathe more in Vermont or New Jersey? What do black women think about Simon & Garfunkel? (Hint: they don’t think about Simon & Garfunkel.) Rudder also traces human migration over time, showing how groups of people move from certain small towns to the same big cities across the globe. And he grapples with the challenge of maintaining privacy in a world where these explorations are possible.   Visually arresting and full of wit and insight, Dataclysm is a new way of seeing ourselves—a brilliant alchemy, in which math is made human and numbers become the narrative of our time.

    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

    It took the open source world by storm since its inception in 2005, and is used by small development shops and giants like Google, Red Hat, and IBM, and of course many open source projects.A book by Git experts to turn you into a Git expert. Introduces the world of distributed version control Shows how to build a Git development workflow.

    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.

    But developing these systems brings its own set of headaches. With lots of examples and practical advice, this book takes a holistic view of the topics that system architects and administrators must consider when building, managing, and evolving microservice architectures.Microservice technologies are moving quickly. Author Sam Newman provides you with a firm grounding in the concepts while diving into current solutions for modeling, integrating, testing, deploying, and monitoring your own autonomous services. You'll follow a fictional company throughout the book to learn how building a microservice architecture affects a single domain.Discover how microservices allow you to align your system design with your organization's goalsLearn options for integrating a service with the rest of your systemTake an incremental approach when splitting monolithic codebasesDeploy individual microservices through continuous integrationExamine the complexities of testing and monitoring distributed servicesManage security with user-to-service and service-to-service modelsUnderstand the challenges of scaling microservice architectures

    The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but also provides the background needed to understand how and why these algorithms work. Machine Learning: An Algorithmic Perspective is that text.Theory Backed up by Practical ExamplesThe book covers neural networks, graphical models, reinforcement learning, evolutionary algorithms, dimensionality reduction methods, and the important area of optimization. It treads the fine line between adequate academic rigor and overwhelming students with equations and mathematical concepts. The author addresses the topics in a practical way while providing complete information and references where other expositions can be found. He includes examples based on widely available datasets and practical and theoretical problems to test understanding and application of the material. The book describes algorithms with code examples backed up by a website that provides working implementations in Python. The author uses data from a variety of applications to demonstrate the methods and includes practical problems for students to solve.Highlights a Range of Disciplines and ApplicationsDrawing from computer science, statistics, mathematics, and engineering, the multidisciplinary nature of machine learning is underscored by its applicability to areas ranging from finance to biology and medicine to physics and chemistry. Written in an easily accessible style, this book bridges the gaps between disciplines, providing the ideal blend of theory and practical, applicable knowledge."

    But how do you build the best team organization for your specific goals, culture, and needs? Team Topologies is a practical, step-by-step, adaptive model for organizational design and team interaction based on four fundamental team types and three team interaction patterns. It is a model that treats teams as the fundamental means of delivery, where team structures and communication pathways are able to evolve with technological and organizational maturity.In Team Topologies, IT consultants Matthew Skelton and Manuel Pais share secrets of successful team patterns and interactions to help readers choose and evolve the right team patterns for their organization, making sure to keep the software healthy and optimize value streams.Team Topologies is a major step forward in organizational design for software, presenting a well-defined way for teams to interact and interrelate that helps make the resulting software architecture clearer and more sustainable, turning inter-team problems into valuable signals for the self-steering organization.

    Over the past five years, authors Dustin Boswell and Trevor Foucher have analyzed hundreds of examples of "bad code" (much of it their own) to determine why they’re bad and how they could be improved. Their conclusion? You need to write code that minimizes the time it would take someone else to understand it—even if that someone else is you.This book focuses on basic principles and practical techniques you can apply every time you write code. Using easy-to-digest code examples from different languages, each chapter dives into a different aspect of coding, and demonstrates how you can make your code easy to understand.Simplify naming, commenting, and formatting with tips that apply to every line of codeRefine your program’s loops, logic, and variables to reduce complexity and confusionAttack problems at the function level, such as reorganizing blocks of code to do one task at a timeWrite effective test code that is thorough and concise—as well as readable"Being aware of how the code you create affects those who look at it later is an important part of developing software. The authors did a great job in taking you through the different aspects of this challenge, explaining the details with instructive examples." —Michael Hunger, passionate Software Developer

    For easy use, the lists are organized into ten sections, given here with a sample from each: All About Art ("Elements of Art") ... Art History ("Timelines of Art History") ... For the Art Teacher ("The National Visual Arts Standards") ... Art Materials ("Things to Do with Collage") ... Painting, Drawing & Printmaking ("All About Color Pigment") ... Sculpture ("Master Sculptors & Their Work")... Architecture ("Great Architects of the World")... Fine Arts & Folk Art ("African American Crafts") ... Technology & Art ("The Evolution of Photography") ... Museums ("Museums Devoted to the Work of One Artist").

    Browsers iterate at a remarkable pace. Faced with this volatile landscape we can either struggle for control or we can embrace the inherent flexibility of the web.Responsive design is not just another technique—it is the beginning of the maturation of a medium and a fundamental shift in the way we think about the web.Implementing Responsive Design is a discussion about how this affects the way we design, build, and think about our sites. Readers will learn how to:- Build responsive sites using a combination of fluid layouts, media queries and fluid media- Adopt a responsive workflow from the very start of a project- Enhance content for different devices- Use feature-detection and server-side enhancement to provide a richer experience

    This book claimed that through a piece of software called a "browser," which accesses "web sites," the world economy and our daily lives would change forever. Would you have believed even 10 percent of that book? Did you take advantage of the first Internet wave and get ahead of the curve? "Pull" is the blueprint to the next disruptive wave. Some call it Web 3.0; others call it the semantic web. It's a fundamental transition from pushing information to pulling, using a new way of thinking and collaborating online. Using the principles of this book, you will slash 5-20 percent off your bottom line, make your customers happier, accelerate your industry, and prepare your company for the twenty-first century. It isn't going to be easy, and you don't have any choice. By 2015, your company will be more agile and your processes more flexible than you ever thought possible. The semantic web leads to possibilities straight from science fiction, such as buildings that can order their own supplies, eliminating the IRS, and lawyers finally making sense. But it also leads to major changes in every field, from shipping and retail distribution to health care and financial reporting. Through clear examples, case studies, principles, and scenarios, business strategist David Siegel takes you on a tour of this new world. You'll learn: -Which industries are already ahead. -Which industries are already dead. -How to make the power shift from pushing to pulling information. -How software, hardware, media, and marketing will all change. -How to plan your own strategy for embracing the semantic web. We are at the beginning of a new technology curve that will affect all areas of business. Right now, you have a choice. You can decide to start preparing for the exciting opportunities that lay ahead or you can leave this book on the shelf and get left in the dust like last time.