What is NLP (Natural Language Processing)?
Natural language processing (NLP) is a subfield of artificial intelligence concerned with helping AI chatbots and machines understand and process human language.
NLP combines machine learning, deep learning models, and computational linguistics to process human language.
What are NLP tasks?
A natural language processing (NLP) engine uses tools like natural language understanding (NLU) to analyze sentiment, summarize algorithms, handle tokenization, etc.
Some of the NLP tasks include:
- Speech recognition
- Part of speech tagging or grammatical tagging
- Word sense disambiguation
- Named entity recognition (NER)
- Co-reference resolution
- Sentiment analysis
- Natural language generation
- Machine translation
What are the approaches to NLP?
Some common approaches to NLP are:
- Supervised NLP – in this method, you train the software with labeled or known inputs and outputs. For example, it is used for categorizing documents according to specific labels.
- Unsupervised NLP – is a type of NLP that uses a statistical language model to predict the pattern after giving it non-labeled input. For example, the autocomplete feature in text messages.
- Natural language understanding – this type of NLP analyzes sentence meaning.
- Natural language generation – focuses on making conversational text like humans based on specific keywords or topics.
