About the Author
Russell Jurney cut his data teeth in casino gaming, building web apps to analyze the performance of slot machines in the US and Mexico. After dabbling in entrepreneurship, interactive media and journalism, he moved to silicon valley to build analytics applications at scale at Ning and LinkedIn. He lives on the ocean in Pacifica, California with his wife Kate and two fuzzy dogs.
发表于2024-11-14
Agile Data Science 2024 pdf epub mobi 电子书
这本书的第二版已经于2018年出版了。这第一版面世于2014年,第二版在此基础之上有非常大幅度的修改。但最最基本的思路没有变化:端到端,全栈,敏捷,技术为具体业务服务。 第二版的链接在下面: [Spark全栈数据分析] 对比两个版本,除了内容扩充了不少,处理的问题更加充实,...
评分这本书的第二版已经于2018年出版了。这第一版面世于2014年,第二版在此基础之上有非常大幅度的修改。但最最基本的思路没有变化:端到端,全栈,敏捷,技术为具体业务服务。 第二版的链接在下面: [Spark全栈数据分析] 对比两个版本,除了内容扩充了不少,处理的问题更加充实,...
评分这本书的第二版已经于2018年出版了。这第一版面世于2014年,第二版在此基础之上有非常大幅度的修改。但最最基本的思路没有变化:端到端,全栈,敏捷,技术为具体业务服务。 第二版的链接在下面: [Spark全栈数据分析] 对比两个版本,除了内容扩充了不少,处理的问题更加充实,...
评分这本书的第二版已经于2018年出版了。这第一版面世于2014年,第二版在此基础之上有非常大幅度的修改。但最最基本的思路没有变化:端到端,全栈,敏捷,技术为具体业务服务。 第二版的链接在下面: [Spark全栈数据分析] 对比两个版本,除了内容扩充了不少,处理的问题更加充实,...
评分这本书的第二版已经于2018年出版了。这第一版面世于2014年,第二版在此基础之上有非常大幅度的修改。但最最基本的思路没有变化:端到端,全栈,敏捷,技术为具体业务服务。 第二版的链接在下面: [Spark全栈数据分析] 对比两个版本,除了内容扩充了不少,处理的问题更加充实,...
图书标签: 数据挖掘 数据分析 DataScience 计算机科学 机器学习 数据科学 计算机 大数据
Mining data requires a deep investment in people and time. How can you be sure you're building the right models? What tools help you connect with the customer's needs? With this hands-on book, you'll learn a flexible toolset and methodology for building effective analytics applications. Agile Data shows you how to create an environment for exploring data, using lightweight tools such as Ruby, Python, Apache Pig, and the D3.js (Data-Driven Documents) JavaScript library. You'll learn an iterative approach that allows you to quickly change the kind of analysis you're doing, as you discover what the data is telling you. All the example code in this book is available as working Heroku apps. Build an application to mine your own email inbox Use several data structures to extract multiple features from a single dataset, and learn how different perspectives can yield insight Rapidly boot your applications as simple front-ends to key/value stores Add features driven by descriptive and inferential statistics, machine learning, and data visualization Gather usage data and talk to real users to help guide your data-driven exploration You can provide constructive comments on the manuscript through O'Reilly's Open Feedback Publishing System (OFPS). Learn more at http://labs.oreilly.com/ofps.html.
入门教程,不错
评分入门教程,不错
评分入门教程,不错
评分入门教程
评分入门教程
Agile Data Science 2024 pdf epub mobi 电子书