Overview
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Learn to use natural language processing to make sense of text data and derive useful insights.
Syllabus
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Introduction
- Gain insights from unstructured text data
- What you should know
- Exercise files
- What is named entity recognition (NER)?
- NER with spaCy
- Data preprocessing for custom NER
- Custom model training with spaCy
- Introduction to topic modeling
- Data preprocessing for topic modeling
- Topic modeling with Gensim
- Topic modeling visualization with pyLDAvis
- Model evaluation for topic modeling
- What is text summarization?
- Text extraction for summarization
- Text summarization with sumy
- What is sentiment analysis?
- Sentiment analysis with VADER
- Sentiment analysis with transformers
- Next steps
