Vista normal
Vista MARC
Machine learning models and algorithms for Big Data classification : thinking with examples for effective learning / Shan Suthanharan.
Tipo de material:![Texto](/opac-tmpl/lib/famfamfam/BK.png)
- texto
- sin mediación
- volumen
- 9781489976413
- 1489976418
- QA 76.9.B45 S88.2016
Contenidos:
Science of Information -- Part I Understanding Big Data -- Big Data Essentials -- Big Data Analytics -- Part II Understanding Big Data Systems -- Distributed File System -- MapReduce Programming Platform -- Part III Understanding Machine Learning -- Modeling and Algorithms -- Supervised Learning Models -- Supervised Learning Algorithms -- Support Vector Machine -- Decision Tree Learning -- Part IV Understanding Scaling-Up Machine Learning -- Random Forest Learning -- Deep Learning Models -- Chandelier Decision Tree -- Dimensionality Reduction.
Tipo de ítem | Biblioteca actual | Colección | Signatura topográfica | Copia número | Estado | Fecha de vencimiento | Código de barras | |
---|---|---|---|---|---|---|---|---|
Libros | Biblioteca Francisco Xavier Clavigero Acervo | Acervo General | QA 76.9.B45 S88.2016 (Navegar estantería(Abre debajo)) | ej. 1 | Disponible | UIA184965 |
Navegando Biblioteca Francisco Xavier Clavigero estanterías, Ubicación en estantería: Acervo, Colección: Acervo General Cerrar el navegador de estanterías (Oculta el navegador de estanterías)
QA 76.9.AL73 M3318.1995 Sistemas computacionales / | QA 76.9 B45.2006 Cybersins and digital good deeds : a book about technology and ethics / | QA 76.9.B45 O64.2017 Weapons of math destruction : how big data increases inequality and threatens democracy / | QA 76.9.B45 S88.2016 Machine learning models and algorithms for Big Data classification : thinking with examples for effective learning / | QA 76.9 C47.2016 Internet negro : el lado oscuro de la red / | QA 76.9.C55 H6618.2009 SQL Server, paso a paso / | QA 76.9.C55 M5218.2005 La Biblia de Exchange Server 2003 / |
Incluye referencias bibliográficas e índice.
Science of Information -- Part I Understanding Big Data -- Big Data Essentials -- Big Data Analytics -- Part II Understanding Big Data Systems -- Distributed File System -- MapReduce Programming Platform -- Part III Understanding Machine Learning -- Modeling and Algorithms -- Supervised Learning Models -- Supervised Learning Algorithms -- Support Vector Machine -- Decision Tree Learning -- Part IV Understanding Scaling-Up Machine Learning -- Random Forest Learning -- Deep Learning Models -- Chandelier Decision Tree -- Dimensionality Reduction.