GIAC Machine Learning Engineer - GMLE FREE EXAM DUMPS QUESTIONS & ANSWERS]

Question 1

Which Python libraries are commonly used for visualizing data in machine learning?
(Choose two)
Response:

A. Seaborn B. Pandas C. Matplotlib D. TensorFlow

Discussion 0

Correct Answer: A,C Vote an answer

Question 2

Which loss function is typically used for regression problems?
Response:

A. Cross-entropy loss B. Hinge loss C. Kullback-Leibler divergence D. Mean Squared Error (MSE)

Discussion 0

Correct Answer: D Vote an answer

Question 3

Unsupervised learning is primarily used for:
Response:

A. Classification tasks with predefined categories B. Predicting outcomes based on labeled data C. Finding hidden patterns in unlabeled data D. Regression analysis with continuous output

Discussion 0

Correct Answer: C Vote an answer

Question 4

Which of the following best describes linear regression?
Response:

A. A clustering algorithm B. A technique for predicting a continuous target variable based on input features C. A neural network technique D. A method for classifying data into categories

Discussion 0

Correct Answer: B Vote an answer

Question 5

The 'Pandas' library in Python is primarily used for:
Response:

A. Implementing reinforcement learning algorithms B. Real-time data streaming C. Data manipulation and analysis D. Building neural network models

Discussion 0

Correct Answer: C Vote an answer

Question 6

What is a primary goal of data visualization in machine learning?
Response:

A. To identify patterns and insights in data B. To replace the need for statistical analysis C. To reduce the dimensionality of data D. To optimize the model's performance

Discussion 0

Correct Answer: A Vote an answer

Question 7

Which of the following are common applications of Bayes' Theorem in machine learning?
(Choose two)
Response:

A. Building decision trees B. Calculating the posterior probability in classification tasks C. Creating Naive Bayes classifiers D. Developing recommendation systems

Discussion 0

Correct Answer: B,C Vote an answer

Question 8

Which strategies can be applied to improve the anomaly detection performance of an autoencoder?
(Choose two)
Response:

A. Increase the size of the latent space B. Train the autoencoder on both normal and anomalous data C. Add regularization techniques such as L1 or L2 D. Reduce the number of hidden layers

Discussion 0

Correct Answer: B,C Vote an answer

Question 9

In the context of machine learning, what is a 'loss function' used for?
Response:

A. To select the most important features of the data B. To increase the speed of training C. To reduce the memory usage of the model D. To evaluate the performance of the model

Discussion 0

Correct Answer: D Vote an answer

Question 10

What is Random Forest an example of?
Response:

A. A clustering algorithm B. A neural network architecture C. A reinforcement learning technique D. An ensemble learning method

Discussion 0

Correct Answer: D Vote an answer

Question 11

You have a large dataset stored as a CSV file, and you want to load, clean, and prepare it for a machine learning model using Python. What steps should you take using Pandas to clean the data and remove any rows with missing values?
Response:

A. Use the pd.read_csv() function to load the data, followed by the dropna() function to remove rows with missing values, and the describe() function to get summary statistics for further analysis B. Visualize the missing values with Matplotlib before cleaning the data C. Use np.load() to load the data and ignore any missing values D. Load the data with pd.read_csv() and manually remove missing values from the file

Discussion 0

Correct Answer: A Vote an answer