|
|
|
|
LEADER |
02425nmm a2200469 u 4500 |
001 |
EB001955454 |
003 |
EBX01000000000000001118356 |
005 |
00000000000000.0 |
007 |
cr||||||||||||||||||||| |
008 |
210123 ||| eng |
050 |
|
4 |
|a QA76.9.D343
|
100 |
1 |
|
|a Dix, Paul
|
245 |
0 |
0 |
|a Working with big data
|b infrastructure, algorithms and visualizations : livelessons
|c by Paul Dix
|
246 |
3 |
1 |
|a Infrastructure, algorithms and visualizations
|
260 |
|
|
|a [Indianapolis, Ind.?]
|b Pearson
|c 2013
|
300 |
|
|
|a 1 streaming video file (6 hr., 46 min., 54 sec.)
|
653 |
|
|
|a Data Mining
|
653 |
|
|
|a Algorithms
|
653 |
|
|
|a Business / Data processing / fast / (OCoLC)fst00842293
|
653 |
|
|
|a Gestion / Informatique
|
653 |
|
|
|a Big data / http://id.loc.gov/authorities/subjects/sh2012003227
|
653 |
|
|
|a JavaScript (Computer program language) / http://id.loc.gov/authorities/subjects/sh96004880
|
653 |
|
|
|a Computer algorithms / http://id.loc.gov/authorities/subjects/sh91000149
|
653 |
|
|
|a Algorithmes
|
653 |
|
|
|a Données volumineuses
|
653 |
|
|
|a JavaScript (Langage de programmation)
|
653 |
|
|
|a Data mining / fast / (OCoLC)fst00887946
|
653 |
|
|
|a algorithms / aat
|
653 |
|
|
|a Computer algorithms / fast / (OCoLC)fst00872010
|
653 |
|
|
|a Business / Data processing / http://id.loc.gov/authorities/subjects/sh85018264
|
653 |
|
|
|a JavaScript (Computer program language) / fast / (OCoLC)fst00982071
|
653 |
|
|
|a Data mining / http://id.loc.gov/authorities/subjects/sh97002073
|
653 |
|
|
|a Big data / fast / (OCoLC)fst01892965
|
653 |
|
|
|a Exploration de données (Informatique)
|
041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
989 |
|
|
|b OREILLY
|a O'Reilly
|
490 |
0 |
|
|a LiveLessons
|
500 |
|
|
|a Title from title screen
|
856 |
4 |
0 |
|u https://learning.oreilly.com/videos/~/9780133358964/?ar
|x Verlag
|3 Volltext
|
082 |
0 |
|
|a 000
|
082 |
0 |
|
|a 330
|
520 |
|
|
|a "Working with Big Data: Infrastructure, Algorithms, and Visualizations LiveLessons presents a high level overview of big data and how to use key tools to solve your data challenges. This introduction to the three areas of big data includes: Infrastructure - how to store and process big data ; Algorithms - how to integrate algorithms into your big data stack and an introduction to classification ; Visualizations - an introduction to creating visualizations in JavaScript using D3.js."--Resource description page
|