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)

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

If you are a budding data scientist, or a data analyst with a basic knowledge of R, and want to get into the intricacies of data mining in a practical manner, this is the book for you. No previous experience of data mining is required.

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for unders...(展开全部)

Here's the resource you need if you want to apply today's most powerful data mining techniques to meet real business challenges. Data Mining: Concepts and Techniques equips you with a sound understanding of data mining principles and teaches you proven methods for knowledge discovery in large corporate databases. Written expressly for database practitioners and professionals, ...(展开全部)

作者简介： Robert Layton 计算机科学博士，网络犯罪问题和文本分析方面的专家。多年来一直热衷于Python编程，参与过scikit-learn库等很多开源库的开发，曾担任2014年度“谷歌编程之夏”项目导师。他曾与全球几大数据挖掘公司密切合作，挖掘真实数据并研发相关应用。他的公司dataPipeline为多个行业提供数据挖掘和数据分析解决方案。 译者简介： 杜春晓 英语语言文学学士，软件工程硕士。其他译著有《电子达人——我的第一本Raspberry Pi入门手册》《Python数据分析》。新浪微博：@宜_生。

Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designe...(展开全部)

If you are a programmer who wants to get started with data mining, then this book is for you.

Services like social networks, web analytics, and intelligent e-commerce often need to manage data at a scale too big for a traditional database. Complexity increases with scale and demand, and handling big data is not as simple as just doubling down on your RDBMS or rolling out some trendy new technology. Fortunately, scalability and simplicity are not mutually exclusive—you j...(展开全部)

Web mining aims to discover useful information and knowledge from the Web hyperlink structure, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semistructured and unstructured nature of the Web data and its heterogeneity. It has also developed many of its own...(展开全部)