Hands-On Natural Language Processing

Learn to use natural language processing to make sense of text data and derive useful insights.

Introduction

• Gain insights from unstructured text data
• What you should know
• Exercise files

1. Named Entity Recognition (NER)

• What is named entity recognition (NER)?
• NER with spaCy
• Data preprocessing for custom NER
• Custom model training with spaCy

2. Topic Modeling

• Introduction to topic modeling
• Data preprocessing for topic modeling
• Topic modeling with Gensim
• Topic modeling visualization with pyLDAvis
• Model evaluation for topic modeling

3. Text Summarization

• What is text summarization?
• Text extraction for summarization
• Text summarization with sumy

4. Sentiment Analysis

• What is sentiment analysis?
• Sentiment analysis with VADER
• Sentiment analysis with transformers

Conclusion

• Next steps