AD-304 · Artificial Intelligence/Unsolved PYQ Paper
ARTIFICIAL INTELLIGENCE - MAY 2024 Question Paper
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Unit 17 MarksaExplain the structure and function of a biological neuron compared to an artificial neuron.
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Unit 17 MarksbHow does the McCulloch-Pitts Neuron model contribute to the development of artificial neural networks? Explain.
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Unit 17 MarksaDescribe the architecture and operation of Rosenblatt's Perceptron model in the context of neural networks.
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Unit 17 MarksbHow does the back propagation algorithm enable the neural network to adjust its weights and biases during training? Explain with example.
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Unit 17 MarksaExplain the process of gradient descent and its variations like momentum in the context of optimizing neural network parameters.
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Unit 17 MarksbDiscuss in detail the concept of layers in an artificial neural network and the specific roles of input, hidden, and output layers?
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Unit 17 MarksaDescribe the purpose and construction of a confusion matrix in the context of evaluating classification performance in CNNs.
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Unit 17 MarksbDescribe the various types of layers used in CNNs? How does it differ? Explain.
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Unit 17 MarksaExplain the significance of padding and stride in convolutional operations within CNNs, and how do they affect the output?
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Unit 17 MarksbExplain the concept of bidirectional RNNs and how they differ from traditional RNNs in terms of information processing.
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Unit 17 MarksaHow does Back Propagation Through Time (BPTT) enable RNNs to learn from sequential data, and what challenges does it face? Explain in detail.
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Unit 17 MarksbDiscuss the architecture and functioning of Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) units within RNNs, highlighting their differences and advantages.
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Unit 17 MarksaCompare and contrast the architectural differences between VGG-16 and GoogLeNet, highlighting their strengths and weaknesses in handling complex image recognition tasks.
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Unit 17 MarksbExplain the concept of residual learning in ResNet architectures and how it addresses the challenge of training neural networks.
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Unit 114 MarksWrite a short note on any two : i) Sigmoid ii) Precision iii) F1-score iv) MNIST data set
Go to where you left off?
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