Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics cove...(展开全部)

Though this book is primarily aimed at data analysts and data scientists, it will also help architects, programmers, and practitioners. Knowledge of either Spark or Hadoop would be beneficial. It is assumed that you have basic programming background in Scala, Python, SQL, or R programming with basic Linux experience. Working experience within big data environments is not mandatory.

The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.

Conduct data-driven marketing research and analysis with hands-on examples using Python by leveraging open-source tools and libraries Key Features Analyze marketing data using proper statistical techniques Use data modeling and analytics to understand customer preferences and enhance strategies without complex math Implement Python libraries like DoWhy, Pandas, and Prophet in a business setting with examples and use cases Purchase of the pri

Conduct data-driven marketing research and analysis with hands-on examples using Python by leveraging open-source tools and libraries Key Features Analyze marketing data using proper statistical techniques Use data modeling and analytics to understand customer preferences and enhance strategies without complex math Implement Python libraries like DoWhy, Pandas, and Prophet in a business setting with examples and use cases Purchase of the pri

The revised and updated edition of this bestselling text provides an accessible introduction to the theory and practice of network analysis in the social sciences. It gives a clear and authoritative guide to the general framework of network analysis, explaining the basic concepts, technical measures and reviewing the available computer programs. The book outlines both the theor...(展开全部)

约翰·斯科特，英国埃塞克斯大学社会学教授。出版30余部书，论文近130篇。主要出版物有《企业、阶级和资本主义》，《谁支配英国》，《社会学理论》、《分层和权力》，《社会网络分析》，主编《牛津社会学词典》。他是《社会学评论》杂志的编委，《英国社会学杂志》和《欧洲社会理论杂志》的编委会成员。最近的著述有《社会理论：社会学中的核心问题》，主编《当代50位重要社会学家》。

If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process.

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)

This book is intended for Data Analysts, Scientists, Data Engineers, Statisticians, Researchers, who want to integrate R with their current or future Big Data workflows.It is assumed that readers have some experience in data analysis and understanding of data management and algorithmic processing of large quantities of data, however they may lack specific skills related to R.