From the course: Natural Language Processing in Python
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Assignment: Text summarization - Python Tutorial
From the course: Natural Language Processing in Python
Assignment: Text summarization
For your assignment on text summarization, you have another message from Lexi Kahn. She says, hello, our client would like a short one liner for each book. Could you use text summarization to summarize the descriptions? Thanks, Lexi. Your key objectives are first to apply text summarization to the book description column. And from there, you'll want to review the results to see if they make sense.
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Contents
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Section introduction2m 33s
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Hugging Face overview5m 3s
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Demo: Create a new environment2m 48s
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Sentiment analysis with LLMs5m 15s
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Demo: Basic sentiment analysis pipeline8m 21s
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Demo: Timing, logging, and device setup4m 33s
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Demo: Compare sentiment scores7m 7s
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Pro tip: Speed up transformers code5m 31s
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Assignment: Sentiment analysis with LLMs1m 32s
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Solution: Sentiment analysis with LLMs9m 9s
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Named entity recognition (NER)5m 2s
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Demo: Basic NER pipeline3m 8s
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Demo: Hugging Face Model Hub2m 23s
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Demo: Clean NER output7m 35s
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Assignment: NER51s
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Solution: NER14m 53s
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Zero-shot classification4m 16s
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Demo: Zero-shot classification7m 7s
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Assignment: Zero-shot classification32s
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Solution: Zero-shot classification5m
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Text summarization3m
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Demo: Text summarization3m 22s
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Demo: Multiple pipelines7m 26s
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Assignment: Text summarization27s
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Solution: Text summarization4m 50s
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Pro tip: Text generation3m 38s
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Document embeddings2m 59s
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Cosine similarity5m 5s
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Document similarity with embeddings2m
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Demo: Feature extraction and embeddings10m 17s
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Demo: Cosine and document similarity5m 58s
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Pro tip: Recommender function12m 55s
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Assignment: Document similarity48s
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Solution: Document similarity6m 10s
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Key takeaways2m 52s
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