Identifying Patterns
Learning Outcomes
Get More Info
data, Tech & ai skills in
What’s Included
Identifying Patterns
Identifying Patterns
Many datasets can contain patterns or trends of interest to businesses. These patterns can be uncovered using unsupervised learning methods. Learn how this works in this lesson.
Where Can Patterns be Found
Where Can Patterns be Found
Unsupervised learning has a variety of use cases of relevance to business. This lesson introduces some of these, and discusses the advantages and disadvantages of the technique.
Introducing Your Case Study
Introducing Your Case Study
In this course, we'll consider the case study of an electrical retailer that can use unsupervised learning to help its expansion into a new city. Learn more about the company in this lesson.
Introducing Clustering
Introducing Clustering
Cluster analysis is a common unsupervised learning technique used to divide the points in a dataset into similar groups or clusters. This lesson will introduce the general topic of cluster analysis.
The K-Means Process
The K-Means Process
The k-means algorithm is the most popular algorithm used in cluster analysis. In this lesson, we'll introduce the intuition behind the algorithm and show how it works for the data in our case study.
Using K-Means Clustering
Using K-Means Clustering
K-means is used in many clustering problems. In this lesson, we'll discuss how to evaluate its effectiveness, determine the right number of clusters for your data, and understand when it is best to use the algorithm.
Other Clustering Methods
Other Clustering Methods
K-means is not the only clustering method that is available. In this lesson, we'll briefly introduce some other clustering techniques, and consider the basic principles of how they work.
Introducing Association Rules
Introducing Association Rules
Association rules are a useful unsupervised learning technique for finding patterns in a dataset, telling you when certain events occur together. We'll introduce the principles of association rules in this lesson.
Creating Association Rules
Creating Association Rules
There are several different algorithms that can be used to create association rules. We'll introduce the principles behind some of the most common ones in this lesson.
Evaluating Rules
Evaluating Rules
An association rule algorithm generates hundreds of possible associations. Learn how to evaluate rules using the metrics of support, confidence, and lift in this lesson.
Other Uses of Association Rules
Other Uses of Association Rules
Association rules can be used in many different situations beyond market basket analysis. Learn about some of these potential use cases in this lesson.
Certifications
A Learner Experience Designed to Deliver Transformation
How Leading Teams Use Kubicle to Upskill & Excel
