Transform your data into insights with must-know techniques and mathematical concepts to unravel the secrets hidden within your data Key Features Learn practical data science combined with data theory to gain maximum insights from data Discover methods for deploying actionable machine learning pipelines while mitigating biases in data and models Explore actionable case studies to put your new skills to use immediately Purchase of the print or

Sinan Ozdemir是一名数据科学家、创业者和教育工作者。Sinan的学术生涯在约翰?霍普金斯大学（The Johns Hopkins University）渡过，主修数学专业。随后他从事教育事业，曾经在约翰?霍普金斯大学和General Assembly公司举办多次数据科学讲座。在此之后，他创立了旨在通过人工智能技术和数据科学力量帮助企业销售团队的创业公司Legion Analytics。 译者简介 张星辰，北京荣之联科技股份有限公司BI 技术顾问，毕业于重庆邮电大学，具有5年数据相关工作经验，熟悉商业智能和数据可视化，通过了微软数据科学专业认证。 中文版审校人 鲜思东，重庆邮电大学教授，硕士生导师，复杂系统智能分析与决策重庆市高校重点实验室副主任，中国商业统计学会理事。现任国际期刊《Advancements in Case Studies》...(展开全部)

Transform your data into insights with must-know techniques and mathematical concepts to unravel the secrets hidden within your data Key Features Learn practical data science combined with data theory to gain maximum insights from data Discover methods for deploying actionable machine learning pipelines while mitigating biases in data and models Explore actionable case studies to put your new skills to use immediately Purchase of the print or

The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contribution...(展开全部)

This title now updated: the definitive neuroscience resource-from Eric R. Kandel, MD (winner of the Nobel Prize in 2000); James H. Schwartz, MD, PhD; Thomas M. Jessell, PhD; Steven A. Siegelbaum, PhD; and A. J. Hudspeth, PhD 900 full-color illustrations. Deciphering the link between the human brain and behavior has always been one of the most intriguing - and often challenging-...(展开全部)

This book is intended for use in a one- or two-semester course in environmental science, human ecology, or environmental studies at the college or advanced placement high school level. Because most students who will use this book are freshman or sophomore nonscience majors, the authors have tried to make the text readable and accessible without technical jargon or a presumption...(展开全部)

This book is intended for use in a one- or two-semester course in environmental science, human ecology, or environmental studies at the college or advanced placement high school level. Because most students who will use this book are freshman or sophomore nonscience majors, the authors have tried to make the text readable and accessible without technical jargon or a presumption...(展开全部)

This title now updated: the definitive neuroscience resource-from Eric R. Kandel, MD (winner of the Nobel Prize in 2000); James H. Schwartz, MD, PhD; Thomas M. Jessell, PhD; Steven A. Siegelbaum, PhD; and A. J. Hudspeth, PhD 900 full-color illustrations. Deciphering the link between the human brain and behavior has always been one of the most intriguing - and often challenging-...(展开全部)

This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, ...(展开全部)

To really learn data science, you should not only master the tools—data science libraries, frameworks, modules, and toolkits—but also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics...(展开全部)