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  1. How can SciPy be used to calculate the cube root of values and exponential values in Python?

  2. Explain how series data structure in Python can be created using dictionary and explicit index values?

  3. Explain the different ways in which data from a series data structure can be accessed in Python?

  4. Explain how the top ‘n’ elements can be accessed from series data structure in Python?

  5. How can SciPy be used to calculate the eigen values and eigen vectors of a matrix in Python?

  6. How can discrete Fourier transform be performed in SciPy Python?

  7. Explain how the minimum of a scalar function can be found in SciPy using Python?

  8. Explain how Nelder-Mead algorithm can be implemented using SciPy Python?

  9. Explain the basics of scikit-learn library in Python?

  10. How can scikit-learn library be used to load data in Python?

  11. How can Seaborn library be used to display kernel density estimations in Python?

  12. What is SciPy in Python? Explain how it can be installed, and its applications?

  13. How to avoid the points getting overlapped while using stripplot in categorical scatter plot Seaborn Library in Python?

  14. Explain how scikit-learn library can be used to split the dataset for training and testing purposes in Python?

  15. How can decision tree be used to implement a regressor in Python?

  16. How to eliminate mean values from feature vector using scikit-learn library in Python?

  17. How can data be scaled using scikit-learn library in Python?

  18. Explain how L1 Normalization can be implemented using scikit-learn library in Python?

  19. How can SciPy be used to calculate the determinant value of a matrix in Python?

  20. Explain how the bottom ‘n’ elements can be accessed from series data structure in Python?
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