Data Science For Decision Makers Jon Howells by Jon Howells 9781837637294, 1837637296 instant download after payment.

Bridge the gap between business and data science by learning how to interpret machine learning and AI models, manage data teams, and achieve impactful results Key Features: - Master the concepts of statistics and ML to interpret models and guide decisions - Identify valuable AI use cases and manage data science projects from start to finish - Empower top data science teams to solve complex problems and build AI products - Purchase of the print Kindle book includes a free PDF eBook Book Description: As data science and artificial intelligence (AI) become prevalent across industries, executives without formal education in statistics and machine learning, as well as data scientists moving into leadership roles, must learn how to make informed decisions about complex models and manage data teams. This book will elevate your leadership skills by guiding you through the core concepts of data science and AI. This comprehensive guide is designed to bridge the gap between business needs and technical solutions, empowering you to make informed decisions and drive measurable value within your organization. Through practical examples and clear explanations, you'll learn how to collect and analyze structured and unstructured data, build a strong foundation in statistics and machine learning, and evaluate models confidently. By recognizing common pitfalls and valuable use cases, you'll plan data science projects effectively, from the ground up to completion. Beyond technical aspects, this book provides tools to recruit top talent, manage high-performing teams, and stay up to date with industry advancements. By the end of this book, you'll be able to characterize the data within your organization and frame business problems as data science problems. What You Will Learn: - Discover how to interpret common statistical quantities and make data-driven decisions - Explore ML concepts as well as techniques in supervised, unsupervised, and reinforcement learning - Find out how to evaluat