Machine Learning Python | Principal Component Analysis (PCA) in AWS Sagemaker [ Project1]
In this video we will teach you how to perform Principal Component Analysis in AWS Sagemake over US-Census data in Python. Principal component analysis, or PCA, is a statistical procedure that allows you to summarize the information content in large data tables by means of a smaller set of “summary indices” that can be more easily visualized and analyzed.
The lab will cover the following steps
1: Data Import
2: Exploratory Data Analysis
3: Data Modeling
4: Accessing PCA Model Attributes
5: Model Deployment and Conclusion
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