Data Mining Fundamentals Playlist

Data Mining Fundamentals

Scatter Plots & Contour Plots – Data Mining Fundamentals Part 24

Data Science Dojo January 7, 2017

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In the final video in our Data Mining Fundamentals series, we conclude our discussion of different visualization techniques for data exploration with scatter plots and contour plots. We will define each plot, and share examples of when you can use …

02:59

Histograms & Box Plots – Data Mining Fundamentals Part 23

Data Science Dojo January 6, 2017

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Histograms and box plots are the most popular visualization techniques. In this tutorial, we discuss the unique benefits of both, and provide examples of when you can use each for your data exploration and visualization.

Part 24:
Scatter Plots …

02:59

Center and Spread Measurement – Data Mining Fundamentals Part 22

Data Science Dojo January 6, 2017

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Center and Spread measurement is the next topic in our discussion on 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.

Part 23…

02:55

Data Visualization & Exploration – Data Mining Fundamentals Part 21

Data Science Dojo January 6, 2017

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Data exploration is visualization and calculation to better understand characteristics of data. We will tell you the key motivations of data exploration as well as the techniques used in data exploration.

Part 22:
Center and Spread Measurement

Part 20…

03:06

Summary Statistics – Data Mining Fundamentals Part 20

Data Science Dojo January 6, 2017

891 1

Summary statistics are numbers that summarize properties of data, and the frequency of an attribute value is a percentage measuring how often the value occurs in the data set. We will also describe percentiles, and provide examples of each.

Part …

02:38

Evaluating Correlation – Data Mining Fundamentals Part 19

Data Science Dojo January 6, 2017

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Correlation and visually evaluating is the next step in our discussion on similarity and dissimilarity. Correlation measures the linear relationship between objects, and to visually evaluate correlation, you will need to build a scatter plot.

Part 20:
Evaluating Correlation…

Euclidian Distance and Cosine Similarity

04:29

Euclidean Distance & Cosine Similarity – Data Mining Fundamentals Part 18

Data Science Dojo January 6, 2017

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Euclidean distance and cosine similarity are the next aspect of similarity and dissimilarity we will discuss. We will show you how to calculate the euclidean distance and construct a distance matrix.
This series is part of our pre-bootcamp course work …

data mining Similarity and Dissimilarity

03:03

Similarity and Dissimilarity – Data Mining Fundamentals Part 17

Data Science Dojo January 6, 2017

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Similarity and dissimilarity are the next data mining concepts we will discuss. Similarity is a numerical measure of how alike two data objects are, and dissimilarity is a numerical measure of how different two data objects are. We also discuss …

03:01

Data Transformation – Data Mining Fundamentals Part 16

Data Science Dojo January 6, 2017

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We discuss the transformation of data in data preprocessing, such as attribute transformation. Attribute transformation is a function that maps the entire set of values of a given attribute to a new set of replacement values such that each old …

04:45

Feature Selection – Data Mining Fundamentals Part 15

Data Science Dojo January 6, 2017

700 1

Feature selection is another way of performing dimensionality reduction. We discuss the many techniques for feature subset selection, including the brute-force approach, embedded approach, and filter approach. Feature subset selection will reduce redundant and irrelevant features in your data.

Part …