Part four of data exploration and visualization, we discuss different visualization techniques starting with the most popular histograms and box plots.

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In this next section we introduce you to similarity and dissimilarity.

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In part seven of data preprocessing, we discuss transformation of data such as attribute transformation.

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Part five of data exploration and visualization, we continue our discussion of different visualization techniques to scatter plots and contour plots.
This concludes our Data Mining Fundamentals course.

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Part three of data exploration and visualization, we discuss measuring of center such as the median and mean. And look at measures of spread such as range and variance.

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Part two of data exploration and visualization, we discuss summary statistics and the frequency and mode of a attribute.

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In our last section in data mining fundamentals, we introduce you to data exploration and visualization and what they are to data mining.

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Part three of our introduction to similarity and dissimilarity, we discuss correlation and visually evaluating it.

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Part two of our introduction to similarity and dissimilarity, we discuss euclidean distance and cosine similarity.

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In part six of data preprocessing, we discuss another way of dimensionality reduction, feature subset selection.

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