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Erring is human. To err is human. Seeing is believing. To see is to believe. For the given above training data construct a neural architecture

Erring is human. To err is human. Seeing is believing. To see is to believe.
For the given above training data construct a neural architecture for language modelling for the following
case. Menon the dimension at each and every layer and for the weights between layers.
Case: "Using context window of size 4, design a neural network to predict the next word with candidate
vocabulary of size 10. Each vocabulary has a word embedding of dimension 3. Use two internal hidden
layers. First one with 6 neurons and second with 4 neurons. Each internal hidden layer's must be use sigmoid
acvaon funcon."
If the above needs to be changed to accommodate the net to learn the word embedding as well, do the
necessary modicaon in above case study requirement and pictorially draw the nal network (No need to
draw all the connecon between immediate layers).

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