Predictive analytics with Microsoft Azure machine learning : build and deploy actionable solutions in minutes /: build and deploy actionable solutions in minutes. (2015)
- Record Type:
- Book
- Title:
- Predictive analytics with Microsoft Azure machine learning : build and deploy actionable solutions in minutes /: build and deploy actionable solutions in minutes. (2015)
- Main Title:
- Predictive analytics with Microsoft Azure machine learning : build and deploy actionable solutions in minutes
- Further Information:
- Note: Roger Barga, Valentine Fontama and Wee Hyong Tok.
- Authors:
- Barga, Roger S
Fontama, Valentine
Tok, Wee-Hyong - Contents:
- Machine generated contents note:
- Publisher Details:
- Berkley, CA : Apress
- Publication Date:
- 2015
- Copyright Date:
- 2015
- Extent:
- 1 online resource
- Subjects:
- 005.74
Computer science
Information technology -- Management
COMPUTERS -- Desktop Applications -- Databases
COMPUTERS -- Database Management -- General
COMPUTERS -- System Administration -- Storage & Retrieval
Information technology -- Management
Computers -- Software Development & Engineering -- General
Computers -- Database Management -- Data Mining
Software Engineering
Data mining
Electronic data processing
Software engineering
Data mining
Computers -- Computer Science
Program concepts / learning to program
Electronic books - Languages:
- English
- ISBNs:
- 9781484212004
1484212002
1484212010
9781484212011 - Related ISBNs:
- 9781484212011
- Notes:
- Note: Online resource; title from PDF title page (EBSCO, viewed August 31, 2015).
- Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.343074
- Ingest File:
- 01_294.xml