Merge overleaf-2024-02-11-1408 into main

embeddings.tex

@@ -1557,7 +1557,7 @@ \subsection{Word2Vec}
 \caption{Word2Vec CBOW Neural Network architecture}
 \end{figure}
 
-We'll run this implementation in PyTorch, the popular library for building neural network models. The best way to implement Word2Vec, especially if you're dealing with smaller datasets, is using \hyperlink{https://radimrehurek.com/gensim/}{Gensim}, but Gensim abstracts away the layers into inner classes, which makes for a fantastic user experience. But, since we're just learning about them, we'd like to see a bit more explicitly how they work, and PyTorch, although it does not have a native implementation of Word2Vec, lets us see the inner workings a bit more clearly.
+We'll run this implementation in PyTorch, the popular library for building neural network models. The best way to implement Word2Vec, especially if you're dealing with smaller datasets, is using \href{https://radimrehurek.com/gensim/}{Gensim}, but Gensim abstracts away the layers into inner classes, which makes for a fantastic user experience. But, since we're just learning about them, we'd like to see a bit more explicitly how they work, and PyTorch, although it does not have a native implementation of Word2Vec, lets us see the inner workings a bit more clearly.
 
 To model our problem in PyTorch, we'll use the same approach as with any problem in machine learning: