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Principal Component Analysis

What’s after?What’s after?

We used PCA and received modified data, with a smaller dimension. What will be our next step?

As mentioned earlier, the data obtained is used in machine learning models, i.e. PCA basically acts only as a data processing step.

Once you have your data processed by PCA, you can use it in any machine learning model. It can be a model that solves the problem of classification, regression, clustering, etc. As an example, the use of PCA when working with images, because datasets are often large and with a lack of capacity, a dataset with more than 500,000 images can already become difficult to process. A few examples of how PCA can be used on its own:

  • Visualization of multidimensional data
  • Information compression

And examples of when PCA is used as a data process:

  • Data dimension reduction
  • Noise reduction in data

In the following chapters, you will explore in detail some of the most common uses for PCA.

question-icon

Choose the types of data that PCA can work with effectively:

Select a few correct answers

Section 5.

Chapter 2