Data Science - by Field Cady (Hardcover)
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<p/><br></br><p><b> About the Book </b></p></br></br>"Data science is becoming a ubiquitous tool in the business world to help in making business decisions, optimizing existing technologies, and building intelligence into new ones. The author's previous Wiley book was aimed at practitioners of data science, but there is a much larger audience of people in non-technical roles who will need to help to frame data science problems, interpret their results, and make critical decisions. This book is for them."--<p/><br></br><p><b> Book Synopsis </b></p></br></br><p><b>Tap into the power of data science with this comprehensive resource for non-technical professionals</b></p> <p><i>Data Science: The Executive Summary - A Technical Book for Non-Technical Professionals</i> is a comprehensive resource for people in non-engineer roles who want to fully understand data science and analytics concepts. Accomplished data scientist and author Field Cady describes both the "business side" of data science, including what problems it solves and how it fits into an organization, and the technical side, including analytical techniques and key technologies. </p> <p><i>Data Science: The Executive Summary </i>covers topics like: </p> <ul> <li>Assessing whether your organization needs data scientists, and what to look for when hiring them</li> <li>When Big Data is the best approach to use for a project, and when it actually ties analysts' hands</li> <li>Cutting edge Artificial Intelligence, as well as classical approaches that work better for many problems</li> <li>How many techniques rely on dubious mathematical idealizations, and when you can work around them </li> </ul> <p>Perfect for executives who make critical decisions based on data science and analytics, as well as mangers who hire and assess the work of data scientists, <i>Data Science: The Executive Summary</i> also belongs on the bookshelves of salespeople and marketers who need to explain what a data analytics product does. Finally, data scientists themselves will improve their technical work with insights into the goals and constraints of the business situation.</p> <p><i> </i></p><p/><br></br><p><b> From the Back Cover </b></p></br></br><p><b>Tap into the power of data science with this comprehensive resource for non-technical professionals</b> <p><i>Data Science: The Executive Summary - A Technical Book for Non-Technical Professionals</i> is a comprehensive resource for people in non-engineering roles who want to fully understand data science and analytics concepts. Accomplished data scientist and author Field Cady describes both the "business side" of data science, including what problems it solves and how it fits into an organization, and the technical side, including analytical techniques and key technologies. <p><i>Data Science: The Executive Summary</i> covers topics like: <ul> <li>Assessing whether your organization needs data scientists, and what to look for when hiring them</li> <li>When Big Data is the best approach to use for a project, and when it actually ties analysts' hands</li> <li>Cutting edge Artificial Intelligence, as well as classical approaches that work better for many problems</li> <li>The mathematical idealizations that underlie different analytics techniques, how to spot when they aren't true of your data, and what to do in those situations</li> </ul> <p>Perfect for executives who make critical decisions based on data science and analytics, as well as mangers who hire and assess the work of data scientists, <i>Data Science: The Executive Summary</i> also belongs on the bookshelves of salespeople and marketers who need to explain what a data analytics product does. Finally, data scientists can have more impact by thinking about the goals and constraints that come from the business situation.<p/><br></br><p><b> About the Author </b></p></br></br><p><b>Field Cady, </b> is a data scientist and author in the Seattle area. Most of his career has focused on consulting, for clients of all sizes in a range of industries. More recently he focused on using AI to mine scientific literature at the Allen Institute for Artificial Intelligence. His previous book, <i>The Data Science Handbook</i>, was published in 2017. His work has been covered in Wired, MIT Press and the Wall Street Journal among others.
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