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CIS520 Machine Learning | Lectures / Big Data
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Big Data

 
  • Big Data
    • What is it?
    • Why is it hot?
    • Big n vs big p
    • How is big data different?
      • use available large-scale data
        • rather than hoping for annotated data
      • memorization works well
        • non-parametric methods
 Δ
  • combine multiple data sources
  • Why does it work?
  • How to handle it?
    • Dimensionality reduction
    • Hadoop/MapReduce
    • Sampling (not covered much this year!)

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Page last modified on 01 December 2015 at 09:24 PM