Build NLP systems from tokenization to transformer models. Classify text, extract entities, summarize documents, and deploy as APIs.
Student builds a text preprocessor that removes stop words and punctuation, demonstrating basic NLP skills with Python and NLTK.
Student builds a sentiment analyzer that classifies movie reviews as positive or negative, showcasing sentiment analysis skills with spaCy.
Student builds a named entity recognition model that identifies entities in text, demonstrating entity recognition skills with Hugging Face and Transformers.
Student builds a simple language translator that translates text from one language to another, demonstrating machine translation skills with Googletrans and Python.
Student builds a text summarizer that summarizes long pieces of text into shorter summaries, showcasing text summarization skills with NLTK and spaCy.
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