However, before jumping straight to the coding section, we will first briefly review some of the most commonly used word embedding techniques, along with their pros and cons. In this article we will implement the Word2Vec word embedding technique used for creating word vectors with Python's Gensim library. This video lecture from the University of Michigan contains a very good explanation of why NLP is so hard. This is a huge task and there are many hurdles involved. The task of Natural Language Processing is to make computers understand and generate human language in a way similar to humans. If you want to tell a computer to print something on the screen, there is a special command for that. On the contrary, computer languages follow a strict syntax. Natural languages are always undergoing evolution. For instance, a few years ago there was no term such as 'Google it', which refers to searching for something on the Google search engine. There are multiple ways to say one thing.Īnother important aspect of natural languages is the fact that they are consistently evolving. This is because natural languages are extremely flexible. You immediately understand that he is asking you to stop the car. Suppose, you are driving a car and your friend says one of these three utterances: 'Pull over', 'Stop the car', 'Halt'.

Natural languages are highly very flexible. However, there is one thing in common in natural languages: flexibility and evolution. The rules of various natural languages are different. Languages that humans use for interaction are called natural languages.

The language plays a very important role in how humans interact.

This ability is developed by consistently interacting with other people and the society over many years. Humans have a natural ability to understand what other people are saying and what to say in response.

Gensim python