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Machine Learning with Python: Real-World MCQ Practice Tes


Scenario-Based MCQ on libraries like scikit-learn, TensorFlow, and Keras to teach basic machine learning concepts.

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Question 1:

Which of the following libraries is commonly used for implementing machine learning algorithms in Python?

a) Matplotlib

b) TensorFlow

c) NumPy

d) Django

Question 2:

In a supervised learning problem, what is the role of labeled data?

a) It is not required in supervised learning.

b) Labeled data is used for training the model.

c) Labeled data is used for testing the model.

d) Labeled data is only used for validation.

Question 3:

What is the purpose of the scikit-learn library in the context of machine learning with Python?

a) It is used for web development.

b) It provides tools for data manipulation and analysis.

c) It offers a variety of machine learning algorithms and tools for building models.

d) It is a database management system.

Question 4:

Which of the following is an unsupervised learning algorithm?

a) Linear Regression

b) Decision Trees

c) K-Means Clustering

d) Support Vector Machines (SVM)

Question 5:

What is the primary goal of feature scaling in machine learning?

a) To convert categorical variables into numerical ones.

b) To normalize the range of independent variables or features of the data.

c) To add more features to the dataset.

d) To remove outliers from the dataset.

Question 6:

Which Python library is commonly used for neural network implementations?

a) Scrapy

b) Keras

c) Requests

d) BeautifulSoup

Question 7:

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

a) To train the model on the entire dataset.

b) To evaluate the model's performance on the training data.

c) To divide the dataset into two subsets for training and testing the model.

d) To split the dataset based on the target variable.

Question 8:

In the context of machine learning, what is cross-validation used for?

a) To create a backup of the dataset.

b) To test the model's performance on unseen data.

c) To evaluate the model's performance using multiple subsets of the data.

d) To preprocess the data before training the model.

Question 9:

Which algorithm is commonly used for classification tasks in machine learning?

a) K-Means Clustering

b) Decision Trees

c) Principal Component Analysis (PCA)

d) Linear Regression

Question 10:

What is the purpose of hyperparameter tuning in machine learning?

a) To optimize the model parameters during training.

b) To increase the number of features in the dataset.

c) To visualize the data distribution.

d) To clean the dataset from missing values.

Feel free to expand on these questions or modify them based on the specific topics you want to cover in your practice test. Additionally, you can add explanations and answer keys for each question to enhance the educational value of the practice test.

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