What you would learn in Hands-On Natural Language Processing course?
The ability to extract insight from text data can be an advantage for companies and individual contributors. This course, taught by an instructor, Wuraola Olaoyewusi, is created to help developers understand the text information and improve its value. This is a hands-on class that teaches the practical application of critical natural processing tasks in the field of language. Learn how to apply the lessons learned to the data you use. This course provides a brief overview of each task's flow, use cases, and a coding demonstration. The topics included are recognized entity recognition such as text summarization, topic modeling, and sentiment analysis.
Course Content:
- Introduction
- 1. Named Entity Recognition (NER)
- 2. Topic Modeling
- 3. Text Summarization
- 4. Sentiment Analysis
- Conclusion
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