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OSU Module 18 - Unsupervised Machine Learning

Transformations

  • Take raw data and make it easier to understand. Pre-process data into correct format with only numerical values.

Clustering Algorithms

  • Group similar objects into clusters. For example, using a PCA model.

Preparing Data

  • Data Selection - making good choices about which data will be used.
  • Data Processing - organizing the data by formatting, cleaning, and sampling it.
  • Data Transformation - transforming our data into a simpler format for storage and future use, such as a CSV, spreadsheet, or database file.

Tools

  • conda 4.12.0
  • Python 3.7.11
  • scikit-learn 0.24.2
  • plotly 5.6.0
  • pandas 1.3.4

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