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FDA +001

· 2 min read
Gracefullight
Gracefullight
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Big Data​

  • Volume: describes the data size, up to PB
  • Velocity: the speed of data generation and illustrates how fast the datasets are being produced.
  • Variety: the complexity of datasets, with datasets including both structured and unstructured data.
  • Veracity: The truthfulness or reliability of the data. large + reliable in order to achieve value in the analysis of it.
  • Value: The worth in information that can be achieved by the processing and analysis of large datasets. It can be measured by an assessment of the other qualities of big data.

ML​

  • Supervised learning: uses the old data to learn the relationship between the inputs and outputs, which will be able to predict the outcomes.
    • Decision Trees, Neural Networks, SVM, Random Forests.
  • Unsupervised learning: try to make sense of the data without labelled responses by representing it in another form.
    • Clustering, association rule mining, Neural Networks.

AI​

  • reasoning
  • knowledge representation
  • planning
  • learning
  • natural language processing
  • perception
  • pattern recognition

The Relationships between DA, DS, AI, and ML

Data Science (Second Edition), Chapter 1 - Introduction Pages 1-18, by Vijay Kotu, Bala Deshpande, 2019,

KNIME​

KNIME Flow