Ian H. Witten Data Mining: Practical Machine Learning Tools and Techniques pdf

Data Mining: Practical Machine Learning Tools and Techniques

Ian H. Witten,Ian H. Witten

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Data Mining: Practical Machine Learning Tools and Techniques PDF Télécharger Ebook gratuit Livre France (PDF, EPUB, KINDLE)
Data Mining: Practical Machine Learning Tools and Techniques Télécharger PDF gratuit Livre (PDF, EPUB, KINDLE)
de Ian H. Witten
4,1 sur 5étoiles étoiles sur 5 (50 Commentaires client)
Data Mining: Practical Machine Learning Tools and Techniques Download eBook PDF e Epub, Livre eBook France [Télécharger] Data Mining: Practical Machine Learning Tools and Techniques Format PDF Data Mining: Practical Machine Learning Tools and Techniques PDF Télécharger Ebook gratuit Livre France (PDF, EPUB, KINDLE) [Télécharger] Data Mining: Practical Machine Learning Tools and Techniques en Format PDF
Broché : 654 pages pages
Auteur : Ian H. Witten
Collection : Ian H. Witten
ISBN-10 : 978-0128042915
Format : Format Kindle, Broché
Date de Publication : 17 novembre 2016
Le Titre Du Livre : Data Mining: Practical Machine Learning Tools and Techniques
Moyenne des commentaires client : 4,1 sur 5étoiles étoiles sur 5 50 commentaires client
Nom de fichier : data-mining-practical-machine-learning-tools-and-techniques.pdf
La taille du fichier : 27.03 MB

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Télécharger livre Data Mining: Practical Machine Learning Tools and Techniques de Ian H. Witten [EPUB] – télécharger ebookVous trouverez ci-dessous quelques critiques les plus utiles sur Data Mining: Practical Machine Learning Tools and Techniques. Vous pouvez considérer cela avant de décider d'acheter / lire ce livre.
I've read and reviewed the 1st, 2nd and now the 4th edition. The authors are genuine experts, at the front of their fields, and by adding new contributors have been able to both update existing topics as well as add authoritative treatments of new ones. I recommend this text to anyone seeking a serious introduction to data mining. The emphasis is practical rather than theoretical, but there are pointers to the theoretical literature for those wanting them. The practical emphasis serves those wanting such, and provides motivation and context for the approach. For those with the necessary mathematical, statistical and computing background there are certainly a plethora of more advanced treatments, but Witten et.al. may well be the best available introduction to the subject for almost everyone.

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