Parametry
- 387 stránek
- 14 hodin čtení
Více o knize
When computers harness prior experience to improve future performance, a type of artificial intelligence called machine learning has been applied. The Apache Mahout project is focused on three types of machine learning that are of particular interest to modern web developers "recommendation systems, classification, and clustering. Through real-world examples, Mahout in Action introduces the sorts of problems that these techniques are appropriate for, and then illustrates how Mahout can be applied to solve them. It places particular focus on issues of scalability, and how to apply these techniques at very large scale with the Apache Hadoop framework.
Nákup knihy
Mahout in Action, Sean Owen, Robin Anil, Ted Dunning, Ellen Friedman
- Jazyk
- Rok vydání
- 2011
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Doručení
Platební metody
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- Titul
- Mahout in Action
- Jazyk
- anglicky
- Autoři
- Sean Owen, Robin Anil, Ted Dunning, Ellen Friedman
- Vydavatel
- Manning
- Rok vydání
- 2011
- Vazba
- měkká
- Počet stran
- 387
- ISBN10
- 1935182684
- ISBN13
- 9781935182689
- Série
- Štítky
- Naučná literatura, Společenské vědy, Technologie & Průmysl, Počítače & Internet, USA, Jazyky, Technologie, Algoritmy, Jáva, Java (programovací jazyk), Strojové učení, Apache
- Hodnocení
- 3,65 z 5
- Anotace
- When computers harness prior experience to improve future performance, a type of artificial intelligence called machine learning has been applied. The Apache Mahout project is focused on three types of machine learning that are of particular interest to modern web developers "recommendation systems, classification, and clustering. Through real-world examples, Mahout in Action introduces the sorts of problems that these techniques are appropriate for, and then illustrates how Mahout can be applied to solve them. It places particular focus on issues of scalability, and how to apply these techniques at very large scale with the Apache Hadoop framework.