In this (short) homework, we'll implement Recurrent Neural Networks for character-level language modeling in Python.
We've provided the Linux kernel dataset (data/input.txt) but you're free
to run experiments on a different dataset.
Download the starter code here.
Go through rnn.ipynb and implement the forward and backward pass
for a 'vanilla' RNN. Code to check gradients and sample from the
softmax distribution have already been provided. Implement beam search.
Deliverables
- Completed IPython notebook
rnn.ipynb- Forward pass (10 points)
- Backward pass (10 points)
- Beam search (10 points)
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