Natural Language Processing or NLP is applying machine learning models to text and languages. It is teaching machines to understand what is said in spoken and written word is the focus of natural language processing (NLP). Whenever we dictate something into our iphone/android device that is then converted to text, that’s an NLP algorithm in action. Basically the computer has to be able to communicate with a human. This is called natural language processing (NLP).
- We can use NLP on a text review to predict if the review is a good one or a bad one.
- Natural Language Processing or NLP can be used on a book to predict the genre of the book.
- Going further, we can use NLP to build a machine translator or a speech recognition system.
Speaking of classification algorithms, most of NLP algorithms are classification models, and they include logistic regression, naive bayes, CART which is a model based on decision trees.
A very well known model in NLP is the bag of words model. It is a model used to preprocess the texts to classify before fitting the classification algorithms on the observations containing the texts.
- NLP is an area of computer science and artificial intelligence concerned with the interactions between computers & human (natural) languages. NLP is used to apply machine learning models to text & languages.
- Natural Language Processing (NLP) can be defined as the ability of a machine to analyze,understand & generate human speech.
Main Natural Language Processing (NLP) library examples:-
- Natural language toolkit – NLTK
- Stanford NLP
- Open NLP
Bag of words NLP model includes two things:-
- A vocabulary of known words.
- A measure of the presence of known words.
Two main components of NLP
Two main components of NLP are as follows:-
- Natural Language Understanding (NLU)
- Natural Language Generation (NLG)
How is natural language processing used today?
Most common applications for NLP today are:
- Spam filters
- Algorithmic trading
- Answering questions
- Summarizing information