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© 2025 AIML MCQ
AI & Machine Learning MCQ
40+ Multiple Choice Questions with Detailed Explanations
Practice questions on Machine Learning, Deep Learning, RNN, and Neural Networks
All Questions (Mixed)
40 Questions2
What is a convolutional neural network (CNN) primarily used for?
3
What is a Recurrent Neural Network (RNN) best suited for?
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What is a perceptron?
5
Which algorithm is used for classification problems?
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What is the purpose of the activation function in neural networks?
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What problem do LSTM networks solve?
8
What is the ReLU activation function?
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What is overfitting in machine learning?
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What is backpropagation?
11
What are the three gates in an LSTM cell?
12
What is the purpose of the softmax function?
13
Which technique is used to prevent overfitting?
14
What is dropout in deep learning?
15
What is a GRU (Gated Recurrent Unit)?
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What is weight initialization?
17
What does the bias-variance tradeoff represent?
18
What is a pooling layer in CNN?
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What is bidirectional RNN?
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What is a hidden layer in a neural network?
21
What is cross-validation used for?
22
What is transfer learning?
23
What is teacher forcing in RNN training?
24
What is the loss function used for?
25
Which is an example of unsupervised learning?
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What is batch normalization?
27
What is sequence-to-sequence (Seq2Seq) modeling?
28
What is gradient descent?
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What is the purpose of feature scaling?
30
Which optimizer is commonly used in deep learning?
31
What is the attention mechanism in RNNs?
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What is the learning rate in neural networks?
33
What is a decision tree?
34
What is the vanishing gradient problem?
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What is a common application of RNNs?
36
What is an epoch in neural network training?
37
What is ensemble learning?
38
What is a GAN (Generative Adversarial Network)?
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What is the exploding gradient problem in RNNs?
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