At the same time, Steve Jobs was being forced out of his beloved Apple and starting over with a new company, NeXT Computer. His goal was to build a supercomputer with the power to transform education. Menuez had found his story: he proposed to photograph Jobs and his extraordinary team as they built this new computer, from conception to product launch. In an amazing act of trust, Jobs granted Menuez unlimited access to the company, and, for the next three years, Menuez was able to get on film the spirit and substance of innovation through the day-to-day actions of the world’s top technology guru. From there, the project expanded to include the most trailblazing companies in Silicon Valley, all of which granted Menuez the same complete access that Jobs had. Menuez photographed behind the scenes with John Warnock at Adobe, John Sculley at Apple, Bill Gates at Microsoft, John Doerr at Kleiner Perkins, Bill Joy at Sun Microsystems, Gordon Moore and Andy Grove at Intel, Marc Andreessen at Netscape, and more than seventy other leading companies and innovators. It would be fifteen years before Menuez stopped taking pictures, just as the dotcom bubble burst. An extraordinary era was coming to its close. With his singular behind-the-scenes access to these notoriously insular companies, Menuez was present for moments of heartbreaking failure and unexpected success, moments that made history, and moments that revealed the everyday lives of the individuals who made it happen. This period of rapid, radical change would affect almost every aspect of our culture and our lives in ways both large and small and would also create more jobs and wealth than any other time in human history. And Doug Menuez was there, a witness to a revolution. In more than a hundred photographs and accompanying commentary, Fearless Genius captures the human face of innovation and shows what it takes to transform powerful ideas into reality.

    Now, for the first time, leading agile methodologist Scott Ambler and renowned consultantPramodkumar Sadalage introduce powerful refactoring techniquesspecifically designed for database systems. Ambler and Sadalagedemonstrate how small changes to table structures, data, storedprocedures, and triggers can significantly enhance virtually anydatabase design - without changing semantic

    Meet the Crazy Ones who created Silicon Valley – the hippies who started the Homebrew Computer Club; the young ad executive who first sketched out Apple’s iconic logo; the engineers who met lying down in a cardboard geodesic dome at Stanford University. From Steve Wozniak, who built the first breakthrough Apple computers, to Jony Ive, the young Brit who imagined the iPod - the designers and programmers, the geeks, creatives and dreamers, they are all here.And at the centre of it all, a bearded and barefoot Steve Jobs, whose singular vision would will Apple Inc. into a future that it would come to own …

    Outlook 2007 and 2003 are also covered. This seminal guide presents the author's best practices of time, task, and e-mail management, drawing from time management theories and applying these best practices in Microsoft Outlook. Anyone who finds they are overburdened by e-mail or working too late each day will benefit from this book.

    Norman explores the complex interaction between human thought and the technology it creates, arguing for the development of machines that fit our minds, rather than minds that must conform to the machine.Humans have always worked with objects to extend our cognitive powers, from counting on our fingers to designing massive supercomputers. But advanced technology does more than merely assist with thought and memory—the machines we create begin to shape how we think and, at times, even what we value. Norman, in exploring this complex relationship between humans and machines, gives us the first steps towards demanding a person-centered redesign of the machines that surround our lives.

    Topics are broken down into three major conceptual pieces: Virtualization, Concurrency, and Persistence. Includes all major components of modern systems including scheduling, virtual memory management, disk subsystems and I/O, file systems, and even a short introduction to distributed systems.

     This new edition has an earlier evolution of object concepts, developed in a way that capitalizes on the power of objects without overwhelming beginning programmers. It includes all new Java 5 topics, including Scanner class, enumerated types, autoboxing, variable length parameter lists, the enhanced for loop, and generic types. This is in depth coverage on GUI applications. This book is appropriate for beginning programmers who want to learn to program with Java as well as experienced programmers who want to add Java to their skill-set.

    AI is also behind self-driving cars, predictive policing, and autonomous weapons that can kill without human intervention. These and other AI applications raise complex ethical issues that are the subject of ongoing debate. This volume in the MIT Press Essential Knowledge series offers an accessible synthesis of these issues. Written by a philosopher of technology, AI Ethics goes beyond the usual hype and nightmare scenarios to address concrete questions.Mark Coeckelbergh describes influential AI narratives, ranging from Frankenstein's monster to transhumanism and the technological singularity. He surveys relevant philosophical discussions: questions about the fundamental differences between humans and machines and debates over the moral status of AI. He explains the technology of AI, describing different approaches and focusing on machine learning and data science. He offers an overview of important ethical issues, including privacy concerns, responsibility and the delegation of decision making, transparency, and bias as it arises at all stages of data science processes. He also considers the future of work in an AI economy. Finally, he analyzes a range of policy proposals and discusses challenges for policymakers. He argues for ethical practices that embed values in design, translate democratic values into practices and include a vision of the good life and the good society.

    The many thousands of people who used the system have held on to the PLATO ideas throughout their careers, influencing countless technological products and programs: from flat-panel wall TVs and touch-sensitive screens to chat rooms, instant messaging, screen savers, multiplayer games, flight simulators, crowdsourcing, interactive fiction, emoticons, and e-learning. Fascinating, first hand, and revelatory, The Friendly Orange Glow makes clear that the work of PLATO practitioners has profoundly shaped the computer industry from its inception to our very moment. This book is as much the biography of a vision as it is the story of the people behind PLATO. Every technology story--whether it's about the steam engine, airplane, telephone, Model T, or more recently, Apple, Google, and Tesla electric car--has at its core a vision. It is the immutable nature of technology, and technology visions, to run full life cycles, from cradle to grave. PLATO's story is no different. Like all technology visions, PLATO grew outdated and was disrupted by competing visions. The Friendly Orange Glow is a revelatory paradigm for our technological age.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    You d be up to your neck in normal forms before you even had a chance to wade. When Michael J. Hernandez needed a database design book to teach mere mortals like himself, there were none. So he began a personal quest to learn enough to write one. And he did.Now in its Second Edition, Database Design for Mere Mortals is a miracle for today s generation of database users who don t have the background -- or the time -- to learn database design the hard way. It s also a secret pleasure for working pros who are occasionally still trying to figure out what they were taught.Drawing on 13 years of database teaching experience, Hernandez has organized database design into several key principles that are surprisingly easy to understand and remember. He illuminates those principles using examples that are generic enough to help you with virtually any application.Hernandez s goals are simple. You ll learn how to create a sound database structure as easily as possible. You ll learn how to optimize your structure for efficiency and data integrity. You ll learn how to avoid problems like missing, incorrect, mismatched, or inaccurate data. You ll learn how to relate tables together to make it possible to get whatever answers you need in the future -- even if you haven t thought of the questions yet.If -- as is often the case -- you already have a database, Hernandez explains how to analyze it -- and leverage it. You ll learn how to identify new information requirements, determine new business rules that need to be applied, and apply them.Hernandez starts with an introduction to databases, relational databases, and the idea and objectives of database design. Next, you ll walk through the key elements of the database design process: establishing table structures and relationships, assigning primary keys, setting field specifications, and setting up views. Hernandez s extensive coverage of data integrity includes a full chapter on establishing business rules and using validation tables.Hernandez surveys bad design techniques in a chapter on what not to do -- and finally, helps you identify those rare instances when it makes sense to bend or even break the conventional rules of database design.There s plenty that s new in this edition. Hernandez has gone over his text and illustrations with a fine-tooth comb to improve their already impressive clarity. You ll find updates to reflect new advances in technology, including web database applications. There are expanded and improved discussions of nulls and many-to-many relationships; multivalued fields; primary keys; and SQL data type fields. There s a new Quick Reference database design flowchart. A new glossary. New review questions at the end of every chapter.Finally, it s worth mentioning what this book isn t. It isn t a guide to any specific database platform -- so you can use it whether you re running Access, SQL Server, or Oracle, MySQL or PostgreSQL. And it isn t an SQL guide. (If that s what you need, Michael J. Hernandez has also coauthored the superb SQL Queries for Mere Mortals). But if database design is what you need to learn, this book s worth its weight in gold. Bill CamardaBill Camarda is a consultant, writer, and web/multimedia content developer. His 15 books include Special Edition Using Word 2000 and Upgrading & Fixing Networks for Dummies, Second Edition.

    As the size and complexity of commercial software have grown, the gap between academic computer science and industry has widened. It's an open secret that there is little engineering in software engineering, which continues to rely not on codified scientific knowledge but on intuition and experience.Barr, who worked as a programmer for more than twenty years, describes how the industry has evolved, from the era of mainframes and Fortran to today's embrace of the cloud. He explains bugs and why software has so many of them, and why today's interconnected computers offer fertile ground for viruses and worms. The difference between good and bad software can be a single line of code, and Barr includes code to illustrate the consequences of seemingly inconsequential choices by programmers. Looking to the future, Barr writes that the best prospect for improving software engineering is the move to the cloud. When software is a service and not a product, companies will have more incentive to make it good rather than "good enough to ship."

    Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks.Covering the entry-level topics needed to get you familiar with the basic concepts of machine learning, this guide quickly helps you make sense of the programming languages and tools you need to turn machine learning-based tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data--or anything in between--this guide makes it easier to understand and implement machine learning seamlessly.Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning!

    As the most popular blogging and content management platform available today, WordPress is a powerful tool. This exciting book goes beyond the basics and delves into the heart of the WordPress system, offering overviews of the functional aspects of WordPress as well as plug-in and theme development. What is covered in this book?WordPress as a Content Management System Hosting Options Installing WordPress Files Database Configuration Dashboard Widgets Customizing the Dashboard Creating and Managing Content Categorizing Your Content Working with Media Comments and Discussion Working with Users Managing, Adding, Upgrading, and Using the Theme Editor Working with Widgets Adding and Managing New Plugins Configuring WordPress Exploring the Code Configuring Key Files wp-config.php file Advanced wp-config Options What's in the Core? WordPress Codex and Resources Understanding and customizing the Loop Building A Custom Query Complex Database Operations Dealing With Errors Direct Database Manipulation Building Your Own Taxonomies Plugin Packaging Create a Dashboard Widget Creating a Plugin Example Publish to the Plugin Directory Installing a Theme Creating Your Own Theme How and When to Use Custom Page Templates How to Use Custom Page Templates Pushing Content from WordPress to Other Sites Usability and Usability Testing Getting Your Site Found How Web Standards Get Your Data Discovered Load Balancing Your WordPress Site Securing Your WordPress Site Using WordPress in the Enterprise Is WordPress Right for Your Enterprise? and much more!

    You'll quickly learn the language's fundamentals, then move onto persistence, exception handling, web development, SQLite, data wrangling, and Google App Engine. You'll also learn how to write mobile apps for Android, all thanks to the power that Python gives you.We think your time is too valuable to waste struggling with new concepts. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Python uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.