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Deep Learning By Example by Ahmed Menshawy

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Skip-gram Word2Vec implementation

After understanding the mathematical details of how skip-gram models work, we are going to implement skip-gram, which encodes words into real-valued vectors that have certain properties (hence the name Word2Vec). By implementing this architecture, you will get a clue of how the process of learning another representation works.

Text is the main input for a lot of natural language processing applications such as machine translation, sentiment analysis, and text to speech systems. So, learning a real-valued representation for the text will help us use different deep learning techniques for these tasks.

In the early chapters of this book, we introduced something called one-hot encoding, which produces a vector ...

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