Evan Shellshear

The field of artificial intelligence, data science, and analytics is crippling itself. Exaggerated promises of unrealistic technologies, simplifications of complex projects, and marketing hype are leading to an erosion of trust in one of our most critical approaches to making decisions: data driven. This book aims to fix this by countering the AI hype with a dose of realism. Written by two experts in the field, the authors firmly believe in the power of mathematics, computing, and analytics, but if false expectations are set and practitioners and leaders don’t fully understand everything that really goes into data science projects, then a stunning 80% (or more) of analytics projects will continue to fail, costing enterprises and society hundreds of billions of dollars, and leading to non-experts abandoning one of the most important data-driven decision-making capabilities altogether. For the first time, business leaders, practitioners, students, and interested laypeople will learn what really makes a data science project successful. By illustrating with many personal stories, the authors reveal the harsh realities of implementing AI and analytics.

The field of artificial intelligence, data science, and analytics is crippling itself. Exaggerated promises of unrealistic technologies, simplifications of complex projects, and marketing hype are leading to an erosion of trust in one of our most critical approaches to making decisions: data driven. This book aims to fix this by countering the AI hype with a dose of realism. Written by two experts in the field, the authors firmly believe in the power of mathematics, computing, and analytics, but if false expectations are set and practitioners and leaders don’t fully understand everything that really goes into data science projects, then a stunning 80% (or more) of analytics projects will continue to fail, costing enterprises and society hundreds of billions of dollars, and leading to non-experts abandoning one of the most important data-driven decision-making capabilities altogether. For the first time, business leaders, practitioners, students, and interested laypeople will learn what really makes a data science project successful. By illustrating with many personal stories, the authors reveal the harsh realities of implementing AI and analytics.

The #1 Best Selling Innovation Book On Kindle. Innovation is not just a methodology but a product of hard work and careful risk management. At some point you must grab your tools and get your hands dirty and the best tool you can have is this guide. When you hold this book you are clutching the number one guide to implementing the most successful innovation agenda possible, whether for a startup or established multinational. Full of practical examples, case studies and tips, the low risk innovation techniques presented will guarantee your plans achieve the best outcomes without risking your job or company. The difference between a theory and a success is between these covers. In this book you will learn: -The ins and outs of crowdsourcing -How to leverage hackerspaces and develop your first prototype to launch your product -The best tricks for open innovation -The best kept innovation secret known as behavioral innovation -How access to free knowledge will catalyze your business -The innovation services revolution driven by cloud computing -And the powerful virtuous innovation cycle which is supercharging innovation in all fieldsAs well as much more The topics covered are everything you need to know to be able to innovate as effectively and cheaply as possible. Each of the chapters explores techniques that not only drive innovation but are doing it in a low risk and powerful way.