Python for Data Science and Machine Learning

1.		Which of the following is a method for feature scaling in machine learning?

Standardization

Normalization

Log transformation

All of the above

2.		Which library in Python is used for visualization of data?

Pandas

NumPy

Matplotlib

Scikit-learn

3.		Which library in Python is commonly used for numerical computing and data analysis?

NumPy

Matplotlib

Scikit-learn

TensorFlow

4.		Which library in Python is used for machine learning?

Pandas

NumPy

Scikit-learn

TensorFlow

5.		Which of the following is a Python library for visualization in machine learning?

NumPy

Pandas

Seaborn

Scikit-learn

6.		Which of the following is a type of unsupervised learning in machine learning?

Decision tree

Linear regression

K-means clustering

None of the above

7.		Which of the following is a method for reducing overfitting in machine learning?

Regularization

Gradient descent

Lasso regression

None of the above

8.		Which of the following is not a step in the machine learning process?

Data cleaning and preprocessing

Model selection and training

Hyperparameter tuning

Feature engineering

9.		What is the purpose of the train-test split function in machine learning?

To split the data into training and test sets

To perform cross-validation on the data

To perform hyperparameter tuning on the model

None of the above

10.		Which of the following is a method for selecting the optimal hyperparameters in machine learning?

Grid search

Gradient descent

Lasso regularization

None of the above