Practical data science for the web professional

Michael Nescot

Journal of Digital & Social Media Marketing, 2017, vol. 5, issue 3, 270-279

Abstract: Data science is an increasingly powerful force that is transforming the web and society. While data science is complex and rapidly evolving, interactive, computational tools such as the Jupyter Notebook are making the underlying methods more accessible to diverse audiences, creating new opportunities for collaborative research and sharing data across a range of disciplines and fields. While data science is an essential competitive tool for leading commercial web companies, such tools are also making it a valuable development asset for smaller non-profit and government organisations. Open data science also has potentially significant social benefits in promoting reproducible research and transparency. Data science provides tools and techniques for developing a variety of web applications, while in the process making the web a more distributed, adaptable and personalised network.

Keywords: data science; machine learning; deep learning; natural language; processing; conversational agents; chatbots (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
https://hstalks.com/article/1626/download/ (application/pdf)
https://hstalks.com/article/1626/ (text/html)
Requires a paid subscription for full access.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aza:jdsmm0:y:2017:v:5:i:3:p:270-279

Access Statistics for this article

More articles in Journal of Digital & Social Media Marketing from Henry Stewart Publications
Bibliographic data for series maintained by Henry Stewart Talks ().