Data Science and Machine Learning (Theory and Projects) A to Z - Vanishing Gradients in RNN: GRU
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4 questions
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1.
OPEN ENDED QUESTION
3 mins • 1 pt
What are the advantages of using the tanh activation function over sigmoid and ReLU in recurrent neural networks?
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2.
OPEN ENDED QUESTION
3 mins • 1 pt
Describe the process of how candidate activations are generated in a GRU.
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3.
OPEN ENDED QUESTION
3 mins • 1 pt
What are the learnable parameters in a Gated Recurrent Unit and how are they optimized?
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4.
OPEN ENDED QUESTION
3 mins • 1 pt
Compare the effectiveness of GRUs and LSTMs in handling the vanishing gradient problem.
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