Various Natural Language Processing (NLP) use-cases by using spaCy.
See the Google Colab notebook here for an interactive and visual walk-through of the code by means of different NLP tasks, such as tokenization, Named Entity Recognition (NER), Bag of Words, Word2Vec, text similarity etc.
The basic NLP tasks that this notebook demonstrates are the following:
- Tokenization
- Sentence segmentation or sentence boundary detection
- Part-of-speech (POS) tagging
- Named Entity Recognition (NER) tagging
- Noun Phrase Chunking
- Drawing dependency diagrams or syntactic dependency parsing
- Removal of stop-words & converting texts to lower-cases
- Text & token Similarity
- Computing Bag of Words (BoW)
- Computing TF-IDF (Term Frequency-Inverse Document Frequency)