Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling Understand how use ML tools in real world business problems, where causation matters more that correlation Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.
Innovate your way toward growth using practical, research-backed frameworks The Art of Opportunity offers a path toward new growth, providing the perspective and methods you need to make innovation happen. Written by a team of experts with both academic and industry experience—and a client roster composed of some of the world’s leading companies—this book provides you with the necessary tools to help you capture growth instead of chasing it. The visual frameworks and research-based methodology presented in The Art of Opportunity merge business design thinking and strategic innovation to help you change your growth paradigm. You’ll learn creative and practical methods for exploring growth opportunities and employ a new approach for identifying what “opportunity” looks like in the first place. Put aside the old school way of focusing on new products and new markets, to instead applying value creation to find your new opportunity, craft your offering, design your strategy and build new growth ventures. The changing business ecosystem is increasingly pushing traditional thinking out to pasture. New consumers and the new marketplace are demanding a profound adjustment to the way companies plan and execute growth strategies. This book gives you the tools to create your roadmap toward the new state of growth, and gain invaluable insight into a new way of thinking. The Art of Opportunity will help you to: Start looking at business growth from a new perspective Create value for the customers, company and ecosystem Innovate strategically and design new business models Develop a new active business design thinking approach to innovation Your company’s goal is to grow, and to turn non-customers into customers. The old ways are becoming less tenable and less cost-effective. The Art of Opportunity outlines the new growth paradigm and gives you a solid framework for putting new ideas into practice.
In this book, Spencer Case and Matt Lutz debate whether objective moral facts exist. We often say that actions like murder and institutions like slavery are morally wrong. And sometimes people strenuously disagree about the moral status of actions, as with abortion. But what, if anything, makes statements about morality true? Should we be realists about morality, or anti-realists? After the authors jointly outline the major contemporary positions in the moral realism debate, each author argues for his own preferred views and responds to the other’s constructive arguments and criticisms. Case contends that there are moral truths that don't depend on human beliefs or attitudes. Lutz maintains that there are no moral truths, and even if there were, we wouldn't be in a position to know about them. Along the way, they explore topics like the nature of common sense, the meaning of moral language, and why the realism/anti-realism debate matters. The authors develop their own arguments and responses, but assume no prior knowledge of metaethics. The result is a highly accessible exchange, providing new students with an opinionated gateway to this important area of moral philosophy. But the authors’ originality gives food for thought to seasoned philosophers as well. Key Features Gives a comprehensive overview of all the main positions on moral realism, without assuming any prior knowledge on the subject Features both traditional and original arguments for each position Offers highly accessible language without sacrificing intellectual rigor Draws upon, and builds on, recent literature on the realism/anti-realism debate Uses only a limited number of technical terms and defines all of them in the glossary
Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling Understand how use ML tools in real world business problems, where causation matters more that correlation Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.
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