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)

Enhanced for today's students, the bestselling Foundations of Earth Science returns in a new edition with a bold new look, new contributor Callan Bentley, and a highly anticipated learning path that facilitates active learning. This brief, paperback version of the best-selling Earth Science by Lutgens and Tarbuck is designed for introductory courses in Earth science. It maintai...(展开全部)

For introductory courses in Earth Science. The brief, paperback version of the best-selling Earth Science is designed for introductory courses in earth science. This highly visual, non- technical survey emphasizes broad, up-to-date coverage of basic topics and principles in geology, oceanography, meteorology, and astronomy. The text's flexible design lends itself to the diversi...(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

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)

A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges.

Aho and Ullman have created a C version of their groundbreaking text. As in that text, this book combines the theoretical foundations of computing with essential discrete mathematics. It follows the same organizations as its predecessor, with all examples and exercises in C.

Aho and Ullman have created a C version of their groundbreaking text. As in that text, this book combines the theoretical foundations of computing with essential discrete mathematics. It follows the same organizations as its predecessor, with all examples and exercises in C.

The field of multidimensional data structures is large and growing very quickly. Here, for the first time, is a thorough treatment of multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets. The book includes a thorough introduction; a comprehensive survey to spatial and multidimensional data structures...(展开全部)

This is a pre-1923 historical reproduction that was curated for quality. Quality assurance was conducted on each of these books in an attempt to remove books with imperfections introduced by the digitization process. Though we have made best efforts - the books may have occasional errors that do not impede the reading experience. We believe this work is culturally important and...(展开全部)