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Scalable Machine Learning for Big Data

Abstract
We describe each step along the way to create a scalable machine learning system suitable to process large quantities of data. The techniques described in the report will aid in creating value from a dataset in a scalable fashion while still being accessible to non-specialized computer scientists and computer enthusiasts. Common challenges in the task will be explored and discussed with varying depth. A few areas in machine learning will get particular focus and will be demonstrated with a supplied case-study using weather data courtesy of the Swedish Meteorological and Hydrological Institute.
Degree
Student essay
URI
http://hdl.handle.net/2077/36987
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  • Kandidatuppsatser
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gupea_2077_36987_1.pdf (1012.Kb)
Date
2014-09-22
Author
Bredmar, Fredrik
Andersson, Emanuel
Bogren, Emil
Metadata
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