Applied unsupervised learning with Python : : discover hidden patterns and relationships in unstructured data with Python / / Benjamin Johnston, Aaron Jones, Christopher Kruger.

Saved in:
Bibliographic Details
VerfasserIn:
TeilnehmendeR:
Place / Publishing House:Birmingham, UK : : Packt Publishing,, 2019.
Year of Publication:2019
Language:English
Online Access:
Physical Description:1 online resource (483 pages)
Notes:Includes index.
Tags: Add Tag
No Tags, Be the first to tag this record!
LEADER 01768nam a2200397 i 4500
001 5005781350
003 MiAaPQ
005 20200520144314.0
006 m o d |
007 cr cnu||||||||
008 190617s2019 enk o 001 0 eng d
020 |z 9781789952292 
020 |a 9781789958379 (e-book) 
035 |a (MiAaPQ)5005781350 
035 |a (Au-PeEL)EBL5781350 
035 |a (OCoLC)1104083695 
040 |a MiAaPQ  |b eng  |e rda  |e pn  |c MiAaPQ  |d MiAaPQ 
050 4 |a QA76.73.P98  |b .J646 2019 
082 0 |a 005.133  |2 23 
100 1 |a Johnston, Benjamin,  |e author. 
245 1 0 |a Applied unsupervised learning with Python :  |b discover hidden patterns and relationships in unstructured data with Python /  |c Benjamin Johnston, Aaron Jones, Christopher Kruger. 
264 1 |a Birmingham, UK :  |b Packt Publishing,  |c 2019. 
300 |a 1 online resource (483 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
500 |a Includes index. 
588 |a Description based on print version record. 
590 |a Electronic reproduction. Ann Arbor, MI : ProQuest, 2018. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries. 
650 0 |a Python (Computer program language) 
655 4 |a Electronic books. 
700 1 |a Jones, Aaron,  |e author. 
700 1 |a Kruger, Christopher,  |e author. 
776 0 8 |i Print version:  |a Johnston, Benjamin.  |t Applied unsupervised learning with Python : discover hidden patterns and relationships in unstructured data with Python.  |d Birmingham, UK : Packt Publishing, 2019   |h 483 pages   |z 9781789952292 
797 2 |a ProQuest (Firm) 
856 4 0 |u https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=5781350  |z Click to View