NLP tasks such as document classification, sentiment analysis, clustering, and document summarization require processing and understanding of textual data. Implementation of these tasks depends on how data are being processed and understood by AI systems. One way of doing this is to convert textual representation to a numerical form using some statistical methods such as term frequency-inverse document frequency (TF-IDF), count vector, and so on, but these methods do not consider the meaning ...
3. Introduction to Word Embeddings
Get Hands-on Question Answering Systems with BERT: Applications in Neural Networks and Natural Language Processing now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.