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  1. How can SciPy be used to calculate the inverse of a matrix in Python?

  2. How can non-linear data be fit to a model in Python?

  3. Explain how L2 Normalization can be implemented using scikit-learn library in Python?

  4. How can data be represented visually using ‘seaborn’ library in Python?

  5. How can seaborn library be used to display data without the background axis spines in Python?

  6. Avoid the points getting overlapped without using jitter parameter in categorical scatter plot in Python Seaborn?

  7. How can box and whisker plot be used to compare the data in different categories in Python Seaborn?

  8. Demonstrate the working of violin plots in Python?

  9. How can every violin in a violin plot be split in Python Seaborn Library?

  10. How can bar plot be used in Seaborn library in Python?

  11. How can the countplot be used to visualize data in Python Seaborn Library?

  12. How can Seaborn library be used to visualize point plots in Python?

  13. How can factorplot be used in Seaborn to visualize data in Python?

  14. How can Seaborn library be used to display a hexbin plot in Python?

  15. How can RGB color space be converted to a different color space in Python?

  16. How can scikit-learn be used to convert an image from RGB to grayscale in Python?

  17. How Seaborn library used to display a kernel density estimation plot (joinplot) in Python?

  18. How can data that has multiple variables be visualized using Seaborn in Python?

  19. What is a series data structure in Pandas library in Python?

  20. How can Seaborn library be used to display categorical scatter plots in Python?
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