logo
Product categories

EbookNice.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link.  https://ebooknice.com/page/post?id=faq


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookNice Team

(Ebook) Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information by Jules J. Berman ISBN 9780128156094, 0128156090

  • SKU: EBN-7194204
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

0.0

0 reviews
Instant download (eBook) Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information after payment.
Authors:Jules J. Berman
Pages:449 pages.
Year:2018
Editon:2nd
Publisher:Elsevier
Language:english
File Size:3.24 MB
Format:pdf
ISBNS:9780128156094, 0128156090
Categories: Ebooks

Product desciption

(Ebook) Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information by Jules J. Berman ISBN 9780128156094, 0128156090

Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information, Second Edition updates and expands on the first edition, bringing a set of techniques and algorithms that are tailored to Big Data projects. The book stresses the point that most data analyses conducted on large, complex data sets can be achieved without the use of specialized suites of software (e.g., Hadoop), and without expensive hardware (e.g., supercomputers). The core of every algorithm described in the book can be implemented in a few lines of code using just about any popular programming language (Python snippets are provided).
Through the use of new multiple examples, this edition demonstrates that if we understand our data, and if we know how to ask the right questions, we can learn a great deal from large and complex data collections. The book will assist students and professionals from all scientific backgrounds who are interested in stepping outside the traditional boundaries of their chosen academic disciplines.
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products