Maybe you’re stuck in a boring industry. Maybe your boss likes to slam doors. The truth is that many smart, motivated people would quit in a heartbeat if they weren’t afraid of the financial risks…and, well, the unknown. Whether you want to upgrade your 9-5 or start your own company, Robbie Abed presents a foolproof strategy to find a better job—without stressing, worrying your family, or losing money. You’re talented. Talent is in high demand. You just have to know where to look. In this accessible handbook, full of anecdotes, stories, and tips, you’ll learn how to reconnect with your interests, sharpen your talents, build a network, experiment with ideas for next steps, elicit job offers, and negotiate for higher salaries than your last. Oh, and how to quit your job with aplomb (goodbye email template included). You’ve been miserable for long enough. Look at it this way: hating your job might be the best thing that could’ve happened to you. It’s a kick in the pants to learn survival skills for the coming jobpocalypse. As our machines get smarter, robots, cognitive machines, and the simple software on your computer will render old jobs obsolete. In other words, there is no such thing as job security. The goal of this book is twofold: to help you get out before the music stops, and to teach you skills to find a job you love. Not just once, but anytime, anywhere, in any economic climate, with almost any salary goal. You didn’t hear that wrong.

    Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. Richly illustrated, Complexity: A Guided Tour--winner of the 2010 Phi Beta Kappa Book Award in Science--offers a wide-ranging overview of the ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for its contribution to solving some of the most important scientific questions of our time.

    Most important, it provides a wealth of examples for readers to model for everything from online journal articles to supplemental data sets and measurement instruments to books, videos, apps, websites, podcasts, blog posts, and social media. Approximately 70 examples are provided for readers to consider as they learn how to create reliable references for electronic sources.Students and other writers will find this guide indispensable as well as convenient to download and use when creating a reference list.

    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.

    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

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    according to an artificial intelligence trained by scientist Janelle Shane, creator of the popular blog "AI Weirdness." She creates silly AIs that learn how to name paint colors, create the best recipes, and even flirt (badly) with humans--all to understand the technology that governs so much of our daily lives.We rely on AI every day for recommendations, for translations, and to put cat ears on our selfie videos. We also trust AI with matters of life and death, on the road and in our hospitals. But how smart is AI really, and how does it solve problems, understand humans, and even drive self-driving cars?Shane delivers the answers to every AI question you've ever asked, and some you definitely haven't--like, how can a computer design the perfect sandwich? What does robot-generated Harry Potter fan-fiction look like? And is the world's best Halloween costume really "Vampire Hog Bride"?In this smart, often hilarious introduction to the most interesting science of our time, Shane shows how these programs learn, fail, and adapt--and how they reflect the best and worst of humanity. You Look Like a Thing and I Love You is the perfect book for anyone curious about what the robots in our lives are thinking.

    Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data.

    Mirroring his theory, Minsky boldly casts The Society of Mind as an intellectual puzzle whose pieces are assembled along the way. Each chapter -- on a self-contained page -- corresponds to a piece in the puzzle. As the pages turn, a unified theory of the mind emerges, like a mosaic. Ingenious, amusing, and easy to read, The Society of Mind is an adventure in imagination.

    Contents include: 'Personality Theory in Context', 'Cognitive Personality Theories', 'An Introduction to Intelligence', 'The Application of Personality and Intelligence in Education and the Workplace', 'Optimism', 'Interpersonal Relationships' and 'Psychometric Testing'.

    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!

    You'll learn how to install, configure, operate, manage, and secure the latest release.Covers all the new features and capabilities of the much-anticipated new release of VMware vSphere Discusses the planning, installation, operation, and management for the latest release Reviews migration to the latest vSphere software Offers hands-on instruction and clear explanations with real-world examples Mastering VMware vSphere is the strategic guide you need to maximize the opportunities of virtualization.

    Building on their experience as professional systems analysts and award-winning teachers, authors Dennis, Wixom, and Roth capture the experience of developing and analyzing systems in a way that students can understand and apply.With Systems Analysis and Design, 4th edition , students will leave the course with experience that is a rich foundation for further work as a systems analyst.

     Spot inconsistencies and lies, and apply logic to your daily life. If you want to become a critical, effective, and rational thinker instead of an irrational and snap-judging one, this book is for you. Critical thinking skills strengthen your decision making muscle, speed up your analysis and judgment, and help you spot errors easily. The Critical Mind offers a thorough introduction to the rules and principles of critical thinking. You will find widely usable and situation-specific advice on how to critically approach your daily life, business, friendships, opinions, and even social media. Critical thinking not only saves you time but saves you money and helps you prevent misunderstanding and disappointment. • Learn the main elements of critical thinking. • The theories and practices of the best critical thinkers of the world. • Tips to keep your brain in good shape and receptive to analysis. • Solve your problems with critical thinking. • Become a quicker and better decision maker. Cut out the inefficiencies of your life. The Critical Mind is a guideline for everyone who wishes to learn the basics of critical thinking. If you work in business, education, healthcare, or you study, you’ll find the book equally useful. The book takes a deep look at the framework of geniuses like Richard Paul and Linda Elder to give you a well-established foundation on effective thought. • Become a more effective communicator having relevant argument points. • How to apply critical thinking in a group. • Guiding questions that help you think more critically. • Four types of critical thinking exercise to deepen your knowledge each day. The Critical Mind gives you the best theories and practices to become a more successful and better thinker. Know that the people whom you admire for their mind aren’t aliens, they just use their minds differently. In this book, I unveil how and what they do differently. Delete this. Too repetitive. Put something about the author Discover hidden opportunities, gain a solution-oriented mindset, solve difficult tasks, and understand the world more deeply. Critical thinking will enhance your creativity, logic, intelligence, and helps you navigate through everyday life matters more easily. Think faster, argue better, and succeed consistently.