Download Free 199 Big Machines Book in PDF and EPUB Free Download. You can read online 199 Big Machines and write the review.

Synopsis coming soon.......
Open out the giant fold-out pages to find out about some of the world's biggest, strongest and tallest machines. Full of the world’s biggest machines found on building sites, farms, airports and dockyards including one of the biggest machines ever, the bucket-wheel excavator used in mining. For the biggest of machines, the book includes two giant foldout pages. This attractive picture book format replaces the original board book format, ISBN 9781409507314.
199 clear, labelled illustrations of a variety of waterborne vessels. Find out about the amazing array of ships and boats that sail our oceans and waterways from rowing boats and kayaks to huge luxury liners. Themes include famous ships, sailing ships, all kinds of boats, battleships, submarines and lots more. Great for developing vocabulary and language skills.
Tracy Kidder's "riveting" (Washington Post) story of one company's efforts to bring a new microcomputer to market won both the Pulitzer Prize and the National Book Award and has become essential reading for understanding the history of the American tech industry. Computers have changed since 1981, when The Soul of a New Machine first examined the culture of the computer revolution. What has not changed is the feverish pace of the high-tech industry, the go-for-broke approach to business that has caused so many computer companies to win big (or go belly up), and the cult of pursuing mind-bending technological innovations. The Soul of a New Machine is an essential chapter in the history of the machine that revolutionized the world in the twentieth century. "Fascinating...A surprisingly gripping account of people at work." --Wall Street Journal
As John Connor struggles with fears about his destiny as the head of the human resistance against the robotic forces of Skynet, a new advanced-model Terminator from the future is sent to kill him.
Everything you've always wanted to know about self-driving cars, Netflix recommendations, IBM's Watson, and video game-playing computer programs. The future is here: Self-driving cars are on the streets, an algorithm gives you movie and TV recommendations, IBM's Watson triumphed on Jeopardy over puny human brains, computer programs can be trained to play Atari games. But how do all these things work? In this book, Sean Gerrish offers an engaging and accessible overview of the breakthroughs in artificial intelligence and machine learning that have made today's machines so smart. Gerrish outlines some of the key ideas that enable intelligent machines to perceive and interact with the world. He describes the software architecture that allows self-driving cars to stay on the road and to navigate crowded urban environments; the million-dollar Netflix competition for a better recommendation engine (which had an unexpected ending); and how programmers trained computers to perform certain behaviors by offering them treats, as if they were training a dog. He explains how artificial neural networks enable computers to perceive the world—and to play Atari video games better than humans. He explains Watson's famous victory on Jeopardy, and he looks at how computers play games, describing AlphaGo and Deep Blue, which beat reigning world champions at the strategy games of Go and chess. Computers have not yet mastered everything, however; Gerrish outlines the difficulties in creating intelligent agents that can successfully play video games like StarCraft that have evaded solution—at least for now. Gerrish weaves the stories behind these breakthroughs into the narrative, introducing readers to many of the researchers involved, and keeping technical details to a minimum. Science and technology buffs will find this book an essential guide to a future in which machines can outsmart people.
“Refreshingly thought-provoking...” – The Financial Times The essential playbook for the future of your business What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans it raises profound questions on the future of work and how companies compete. Illustrated with real-world cases, data, and insight, the authors provide clear strategic guidance and actionable steps to help you and your organization move ahead in a world where exponentially developing new technologies are changing how value is created. Written by a team of business and technology expert practitioners—who also authored Code Halos: How the Digital Lives of People, Things, and Organizations are Changing the Rules of Business—this book provides a clear path to the future of your work. The first part of the book examines the once in a generation upheaval most every organization will soon face as systems of intelligence go mainstream. The authors argue that contrary to the doom and gloom that surrounds much of IT and business at the moment, we are in fact on the cusp of the biggest wave of opportunity creation since the Industrial Revolution. Next, the authors detail a clear-cut business model to help leaders take part in this coming boom; the AHEAD model outlines five strategic initiatives—Automate, Halos, Enhance, Abundance, and Discovery—that are central to competing in the next phase of global business by driving new levels of efficiency, customer intimacy and innovation. Business leaders today have two options: be swallowed up by the ongoing technological evolution, or ride the crest of the wave to new profits and better business. This book shows you how to avoid your own extinction event, and will help you; Understand the untold full extent of technology's impact on the way we work and live. Find out where we're headed, and how soon the future will arrive Leverage the new emerging paradigm into a sustainable business advantage Adopt a strategic model for winning in the new economy The digital world is already transforming how we work, live, and shop, how we are governed and entertained, and how we manage our money, health, security, and relationships. Don't let your business—or your career—get left behind. What To Do When Machines Do Everything is your strategic roadmap to a future full of possibility and success. Or peril.
Children need to add lots of words to their spoken vocabularly and this fantastic look-and-talk book will provide them with plenty of opportunities to do so. Images borrowed from Usborne's 1,000 Things...series are collected here in a compact, simplified series for younger children. Thin board will withstand constant use.
This ultimate guide for tech makers covers everything from hand tools to robots plus essential techniques for completing almost any DIY project. Makers, get ready: This is your must-have guide to taking your DIY projects to the next level. Legendary fabricator and alternative engineer Chris Hackett teams up with the editors of Popular Science to offer detailed instruction on everything from basic wood- and metalworking skills to 3D printing and laser-cutting wizardry. Hackett also explains the entrepreneurial and crowd-sourcing tactics needed to transform your back-of-the-envelope idea into a gleaming finished product. In The Big Book of Maker Skills, readers learn tried-and-true techniques from the shop classes of yore—how to use a metal lathe, or pick the perfect drill bit or saw—and get introduced to a whole new world of modern manufacturing technologies, like using CAD software, printing circuits, and more. Step-by-step illustrations, helpful diagrams, and exceptional photography make this book an easy-to-follow guide to getting your project done.
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.