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WorksheetsReview Test Quiz
Total questions: 20
Worksheet time: 10mins
What is the primary purpose of a recurrent neural network (RNN) in natural language processing?
Image classification
Handling sequential data
Speech recognition
Dimensionality reduction
Which layer type is typically used to extract local features in a CNN?
Convolutional layer
Pooling layer
Fully connected layer
Activation layer
What is a Generative Adversarial Network (GAN)?
A network for data analysis
A type of neural network architecture for generative modelling
A network for fast data processing
A network for data encryption
What does the term "transfer learning" mean in the context of deep learning for NLP?
Moving data between servers
Learning from one task and applying it to another
Adjusting learning rates during training
Parallel processing in neural networks
Which of the following is a widely used and effective machine learning algorithm based on the idea of bagging?
Decision Tree
Regression
Classification
Random Forest
You observe the following while fitting a linear regression to the data: As you increase the amount of training data, the test error decreases and the training error increases. The train error is quite low (almost what you expect it to), while the test error is much higher than the train error. What do you think is the main reason behind this behaviour? Choose the most probable option.
High variance
High model bias
High estimation bias
None of the above
refers to a model that can neither model the training data nor generalized to new data.
Good fitting
Overfitting
Underfitting
All of the above
Imagine a new born starts walking. It will try to find a suitable policy to learn to walk after repeated falling and getting up. Specify what type of machine learning algorithm is best suited to do the same.
Supervised learning
Unsupervised learning
Semi-supervised learning
Reinforced learning
The maximum degree of any vertex in a simple graph with n vertices is
n–1
n+1
2n–1
n
What is the purpose of backpropagation in neural networks?
Forward pass to make predictions
Adjusting weights to minimize prediction errors
Activating neurons in the output layer
Normalizing input data
What is the primary objective of deep learning in natural language processing (NLP)?
Image classification
Speech recognition
Pattern recognition in text
Data compression
Identify the correct statement in context of Regressive model of Machine Learning.
Regressive model predicts a numeric value instead of category
Regressive model organizes similar item in your dataset into groups
Regressive model comes up with a set of rules to capture associations between items or events
None of the Mentioned
With the Bayes classifier, missing data items are
Treated as equal compares
Treated as unequal compares
Replaced with a default value.
Ignored
Supervised learning and Unsupervised clustering both require at least one
Hidden attribute
Output attribute
Input attribute
Categorical attribute
In deep learning, which type of neural network architecture is commonly used for image recognition tasks?
Recurrent Neural Network (RNN)
Convolutional Neural Network (CNN)
Long Short-Term Memory (LSTM)
Autoencoder
A simple graph with n vertices and k components can have at most
n edges
n – k edges
(n-k) (n-k-1) /2 edges
(n-k) (n-k+1)/2 edges
If P(a) = 0.4, P(b) = 0.8 and P(B|A) = 0.6 then P(A∪B) is equal to
0.24
0.3
0.48
0.96
What is the main purpose of using a convolutional neural network (CNN) in image recognition tasks?
Handling sequential data
Extracting local features
Speech recognition
Dimensionality reduction
Which type of neural network architecture is commonly used for time series forecasting?
Recurrent Neural Network (RNN)
Convolutional Neural Network (CNN)
Long Short-Term Memory (LSTM)
Autoencoder
What is the primary goal of using a decision tree algorithm in machine learning?
Clustering data points
Creating a linear regression model
Classifying data into categories
Reducing dimensionality of data
