Data Reduction & Exploratory Data Analysis (EDA)
Predictive Analytics
11 Videos | 45m 32s - Includes Assessment
- Earns a Badge
With predictive analytics, relevant data should be stored for easy retrieval and kept up-to-date, with attributes selected contingent on their predictive potential. Explore data reduction and graphic tools for exploratory data analysis.
WHAT YOU WILL LEARN
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recognize key data reduction methodologies
use principal component analysis for feature selection
use the information theory approach for feature selection
recognize the key features of using chi-square
recognize key features of the wrapper data reduction method
recognize the key features of factor analysis -
recognize key features of EDA and how quantitative techniques are used to perform EDA
use box charts and box-and-whisker plots to perform EDA
use run charts and scatter plots to perform EDA
use histograms and stem-and-leaf plots to perform EDA
recognize the use of PCA for feature selection
IN THIS COURSE
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1.Dimension Reduction6m 6sUP NEXT
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2.Principal Component Analysis for Numerical Data3m 20s
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3.Information Theory Approach to Feature Selection4m 20s
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4.Chi-square Feature Selection Method3m 4s
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5.Wrapper Data Reduction Method3m 9s
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6.Factor Analysis3m 13s
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7.Overview of EDA and Quantitative Techniques3m 24s
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8.Bar Charts and Box-and-whisker Plots5m 10s
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9.Run Charts and Scatter Plots2m 59s
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10.Histograms and Stem-and-leaf Plots3m 16s
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11.Exercise: Interpret Scatter Plots2m 31s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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