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)

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)

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)

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

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available in the framework of the data engineering l...(展开全部)

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available in the framework of the data engineering l...(展开全部)

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your appl...(展开全部)

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that ...(展开全部)