Python for Data Science and Machine Learning
Python for Data Science and Machine Learning - Important Points
| 36. | Which of the following is a method for selecting the optimal hyperparameters in machine learning? |
|---|
A. Grid search
B. Gradient descent
C. Lasso regularization
D. None of the above
View Answer Discuss Work SpaceAnswer: option a
Explanation:
Grid search is a method used for selecting the optimal hyperparameters in machine learning, by searching over a predefined grid of hyperparameter values and selecting the best combination.
| 37. | Which of the following is a type of unsupervised learning in machine learning? |
|---|
A. Decision tree
B. Linear regression
C. K-means clustering
D. None of the above
View Answer Discuss Work SpaceAnswer: option c
Explanation:
K-means clustering is a type of unsupervised learning in machine learning, which involves grouping data points into clusters based on their similarity.
| 38. | Which of the following is a method for reducing overfitting in machine learning? |
|---|
A. Regularization
B. Gradient descent
C. Lasso regression
D. None of the above
View Answer Discuss Work SpaceAnswer: option a
Explanation:
Regularization is a method used for reducing overfitting in machine learning, by adding a penalty term to the loss function to discourage complex models.
| 39. | Which of the following is a Python library for optimization in machine learning? |
|---|
A. NumPy
B. Pandas
C. Scikit-learn
D. SciPy
View Answer Discuss Work SpaceAnswer: option d
Explanation:
SciPy is a Python library for optimization in machine learning, providing a wide range of optimization algorithms and functions for numerical computing.