Learn about the K-means method.
- [Instructor] K-means clustering is an unsupervised…machine learning algorithm that you can use…to predict subgroups from within a data set.…With k-means clustering, you usually have an idea…of how many subgroups are appropriate.…With a k-means model, predictions are based on,…one, the number of cluster centers that are present,…and two, the nearest mean values between observations.…Some popular use cases for k-means clustering…are market price and cost modeling, customer segmentation,…hedge fund classification,…and insurance claim fraud detection.…
There are a few things you need to keep in mind…when you're using the k-means model,…the first thing is you always need to scale…your variables before clustering your data, and second,…you need to look at a scatter plot or a data table…to estimate the number of cluster centers…to set for the k parameter in the model.…That might not make a lot of sense to you now,…but I'm going to show you how to do this…in practice in just a few seconds.…All right, let's get some practice with the k-means method.…
AuthorLillian Pierson, P.E.
- Getting started with Jupyter Notebooks
- Visualizing data: basic charts, time series, and statistical plots
- Preparing for analysis: treating missing values and data transformation
- Data analysis basics: arithmetic, summary statistics, and correlation analysis
- Outlier analysis: univariate, multivariate, and linear projection methods
- Introduction to machine learning
- Basic machine learning methods: linear and logistic regression, Naïve Bayes
- Reducing dataset dimensionality with PCA
- Clustering and classification: k-means, hierarchical, and k-NN
- Simulating a social network with NetworkX
- Creating Plot.ly charts
- Scraping the web with Beautiful Soup
Skill Level Beginner
1. Data Munging Basics
2. Data Visualization Basics
3. Basic Math and Statistics
4. Dimensionality Reduction
Explanatory factor analysis6m 39s
5. Outlier Analysis
6. Cluster Analysis
7. Network Analysis with NetworkX
8. Basic Algorithmic Learning
9. Web-based Data Visualizations with Plotly
10. Web Scraping with Beautiful Soup
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