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Clustering Demystified
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Course Content

Clustering Demystified

Clustering Demystified

IntroductionImport Necessary Libraries and DataPreliminary AnalysisData PreparationDeclare Feature Vector and Target VariableConvert Categorical Variable into IntegersFeature ScalingK-Means Model with 2 ClustersCheck the QualityHow many Clusters?K-Means Model with 4 Clusters
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Import Necessary Libraries and Data

Firstly, we need to import all necessary modules, upload the data, and visually examine it.

Modules and methods description

  • numpy (np): Essential for numerical computing and array operations;
  • pandas (pd):
    • read_csv(): Facilitates reading CSV files into DataFrame for data analysis;
    • DataFrame.head(): Offers a quick glimpse of the initial rows in the DataFrame.
  • matplotlib.pyplot (plt): Enables creating various types of plots for data visualization;
  • seaborn (sns): Enhances statistical data visualization based on matplotlib.
Task
test

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  1. Import numpy, pandas, matplotlib.pyplot and seaborn (as np, pd, plt, and sns, respectively).
  2. Read the "Live.csv" file.
  3. Show the first 5 rows of the dataset.

Solution

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Section 1. Chapter 2
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