Agile Data Science 2.0 (O'Reilly)
Agile Data Science 2.0 (O'Reilly)
Monday, 31 July 2017

With a subtitle of Building Full-Stack Data Analytics Applications with Spark,  the revised second edition of this hands-on guide, shows 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.

<ASIN:1491960116>

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.

Author: Russell Jurney
Publisher: O'Reilly
Date: June 2017
Pages: 352
ISBN: 978-1491960110
Print: 1491960116
Kindle: B072MKL34K
Audience: Data scientists
Level: Intermediate

 

 

  • 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

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QlikView Essentials

Author: Chandraish Sinha
Publisher: Packt Publishing
Pages: 166
ISBN: 978-1784397289
Print: 1784397288
Kindle: B016MWREZ8
Audience: QlikView newbies
Rating: 4.8
Reviewer: Ian Stirk

This book aims to introduce you to QlikView, covering the whole application lifecycle, how does it fare?  [ ... ]



The Scrumban (R)Evolution

Author: Ajay Reddy
Publisher: Pearson
Pages:384
ISBN: 978-0134086217
Print: 013408621X
Kindle:B010TQKZ5E
Audience: developers wanting to learn scrumban
Rating: 4.5
Reviewer: Alex Denham

This book sets out to show how Lean and Agile principles can be mixed and managed within the Scrumban framework.


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