Here’s a brief summary of what you’ve learnt so far:

- Applying PCA on a dataset in python
- Evaluate the amount of variance explained by each component
- Use the scree-plot to choose how much variance you need to explain with your transformed dataset
- Transform the dataset to the new chosen Principal Components and then perform dimensionality reduction
- Use the new dataset for visualisation of the observations

Now here are some questions to test your understanding of the same.