Agile Data Science 2.0: Building Full-Stack Data Analytics Applications with Spark
Authors: Russell Jurney
ISBN-10: 1491960116
ISBN-13: 9781491960110
Edition 版本: 1
Released: 2017-06-23
Print Length 页数: 352 pages
Book Description
Data science teams looking to turn research into useful analytics applications require not only the right tools,but also the right approach if they’re to succeed. With the revised second edition of this hands-on guide,up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python,Apache Spark,Kafka,and other tools.
Author Russell Jurney demonstrates how to compose a data platform for building,deploying,and refining analytics applications with Apache Kafka,MongoDB,ElasticSearch,d3.js,scikit-learn,and Apache Airflow. You’ll learn an iterative approach that lets you quickly change the kind of analysis you’re doing,depending on what the data is telling you. Publish data science work as a web application,and affect meaningful change in your organization.
Build value from your data in a series of agile sprints,using the data-value pyramid
Extract features for statistical models from a single dataset
Visualize data with charts,and expose different aspects through interactive reports
Use historical data to predict the future via classification and regression
Translate predictions into actions
Get feedback from users after each sprint to keep your project on track
Preface
1.Setup
1.Theory
2.Agile Tools
3.Data
l1.Climbing the Pyramid
4.Collecting and Displaying Records
5.Visualizing Data with Charts and Tables
6.Exploring Data with Reports
7.Making Predictions
8.Deploying Predictive Systems
9.Improving Predictions
A.Manual Installation
Index
