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on 17-Oct-2025 (Fri)

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Flashcard 7763499814156

Tags
#deep-learning #keras #lstm #python #sequence
Question
Given a standard feedforward MLP network, an RNN can be thought of as the addition of loops to the architecture. For example, in a given layer, each neuron may pass its signal [...] in addition to forward to the next layer. The output of the network may feedback as an input to the network with the next input vector. And so on.
Answer
laterally (sideways)

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Given a standard feedforward MLP network, an RNN can be thought of as the addition of loops to the architecture. For example, in a given layer, each neuron may pass its signal laterally (sideways) in addition to forward to the next layer. The output of the network may feedback as an input to the network with the next input vector. And so on.

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Flashcard 7763501911308

Tags
#ML-engineering #ML_in_Action #learning #machine #software-engineering
Question
business unit members engaged. After all, they really don’t care how many eggs go into the mix, what color the eggs are, or even what species laid the eggs; they just want [...] when it’s done.
Answer
to eat the cake

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business unit members engaged. After all, they really don’t care how many eggs go into the mix, what color the eggs are, or even what species laid the eggs; they just want to eat the cake when it’s done.

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Flashcard 7763503746316

Tags
#deep-learning #keras #lstm #python #sequence
Question
Note that by default, the internal state of the network is reset after each batch, but more explicit control over when the internal state is reset can be achieved by using a so-called stateful LSTM and calling the [...] operation manually
Answer
reset

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, the internal state of the network is reset after each batch, but more explicit control over when the internal state is reset can be achieved by using a so-called stateful LSTM and calling the <span>reset operation manually <span>

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Flashcard 7763505319180

Tags
#recurrent-neural-networks #rnn
Question
We show that incorporating contextual information in the model is straightforward and brings an additional boost in predictive accuracy. However, the model performance is already extremely strong when no context is available beyond the timing of the customer’s transactions. This is welcome news for firms that do not wish [...] on principle, to avoid the questionable ethics of harvesting the ‘‘behavioral surplus”
Answer
to collect personal information

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curacy. However, the model performance is already extremely strong when no context is available beyond the timing of the customer’s transactions. This is welcome news for firms that do not wish <span>to collect personal information on principle, to avoid the questionable ethics of harvesting the ‘‘behavioral surplus” <span>

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