Unsupervised Machine Learning using R

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Learn Path Description

Unsupervised learning methods are central to your journey in data science. Learn how to reduce the number of dimensions in your data set, aggregate data into factors, and cluster your data points to make clear, robust conclusions about your data!

Skills You Will Gain

Courses In This Learning Path

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Total Duration

4 hours

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Level

Intermediate

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Learn Type

Certifications

Unsupervised Learning in R

Machine learning is often used to find patterns in data. It is impossible to predict the future. This is unsupervised learning. This can be used to identify the unsupervised learning that is being done to target marketing campaigns by grouping consumers based on their buying history and demographics. Another example is to determine the unmeasured factors that affect differences in crime rates between cities. This course will give you a general introduction to clustering and dimension in R from a machine learning perspective. This course will allow you to quickly get data into insight.

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Total Duration

4 hours

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Level

Intermediate

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Learn Type

Certifications

Cluster Analysis in R

Cluster analysis is an important tool within the data science toolset. It is used to identify clusters that share similar characteristics. These similarities can be used to help you make better business decisions. It can also help you target different customers in marketing. This course will cover both hierarchical clustering and k-means clustering. These methods will teach you not only how to use them but also how to interpret their results. Three datasets will be used to develop this intuition: longitudinal occupational wage data for soccer players, wholesale customer spending data for wholesale customers, and soccer player positions.

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Total Duration

4 hours

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Level

Intermediate

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Learn Type

Certifications

Factor Analysis in R

This course focuses on the importance of building models that match both data and theories when investigating variables that are not easily quantifiable. It helps you understand dimensionality and perform exploratory and confirmatory factor analyses, which are statistical techniques used to create and refine measures in fields such as economics, psychology, and education. The course also emphasizes the significance of sharing and distributing these measures. By learning how to conduct factor analysis using R, you will gain valuable skills in analyzing and interpreting complex data sets.

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