Advanced analytics with spark patterns for learning from data at scale
In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. You'll...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, California :
O'Reilly
2015.
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| Edición: | First edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628947706719 |
Tabla de Contenidos:
- Analyzing big data
- Introduction to data analysis with Scala and Spark
- Recommending music and the audioscrobbler data set
- Predicting forest cover with decision trees
- Anomaly detection in network traffic with K-means clustering
- Understanding Wikipedia with latent semantic analysis
- Analyzing co-occurrence networks with GraphX
- Geospatial and temporal data analysis on the New York City taxi trip data
- Estimating financial risk through Monte Carlo simulation
- Analyzing genomics data and the BDG project
- Analyzing neuroimaging data with PySpark and Thunder.
