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docs/homeworks/hw2.md

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Install the python package [gensim](https://pypi.org/project/gensim/) which will act as an interface for the GloVe embeddings.
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The following code is provided to you in `word_embeddings.py` to initialize the GloVe model:
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The following code is provided to you in `embeddings.py` to initialize the GloVe model:
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```python
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from gensim.models import KeyedVectors
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### Task
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Implement the `embed` function in the `WordEmbeddings` class in `word_embeddings.py`. `embed` takes in a list of documents and returns the average word embedding for each document using a pre-trained GloVe model.
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Implement the `embed` function in the `WordEmbeddings` class in `embeddings.py`. `embed` takes in a list of documents and returns the average word embedding for each document using a pre-trained GloVe model.
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```python
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docs/past/past.md

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<a href="/nmep/docs/past/fa24.html">Fall 2024</a>
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<a href="https://machine-learning-berkeley.gitbook.io/nmep-website-1">Spring 2024</a>
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<a href="https://machine-learning-berkeley.gitbook.io/nmep-website-1">Fall 2023</a>
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<a href="https://machine-learning-berkeley.gitbook.io/nmep-website-1">Spring 2023</a>
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