Natural-Language-Processing

Natural language processing is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human languages, in particular how to program computers to process and analyze large amounts of natural language data.

Table of content

1. Regular Expressions & Word Tokenization
2. Topic Identification
3. Named Entity Recognition (NER)
4. Building a "Fake News" Classifier
5. Finding words, phrases, names and concepts
6. Data Analysis with SpaCy
7. Processing Pipelines
8. Extension Attributes
9. Scaling and Performance
10. Training A Neural Network Model - I (Training and updating the models)
11. Training A Neural Network Model - II (Training the loop)
12. Training A Neural Network Model - III (Best practices for training models)

References

1. Named Entity Recognition
2. SpaCy
3. Matching and Phrase Matching With SpaCy
4. Annotation With Brat
5. Annotation With Prodigy