AI Fundamentals Part 2 : Introduction to NLP (Natural Language Processing)

What is Natural Language Processing (NLP)?

Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that helps computers understand, interpret and manipulate human language.

NLP involves the application of computational techniques to the analysis and synthesis of natural language and speech.

To analyze natural language and determine the true meaning of text or audio data, it combines machine learning, statistical, and deep learning models with computational linguistics—ruled-based modeling of natural language. It even comprehends the sentiment and intention of the writer or speaker.

NLP processes text and voice data, extracts meaning, determines intent and sentiment, and forms an input or response using computational linguistics, artificial intelligence, and machine learning. Since humans communicate in binary (1 and 0), computers are unable to comprehend or interpret text or words in the same way. As a result, NLP gives computers the ability to comprehend, mimic, and react to people intelligently.

Why is Natural Language Processing important?

Natural language processing is crucial because it aids in the analysis and interpretation of enormous amounts of data. It assists in processing both text and voice data, comprehends intents and feelings, and even aids in the extraction of important insights from the data.

The significance of natural language processing (NLP) lies in its ability to organize unstructured data and lessen ambiguity in natural language. It even assists companies in better organizing their data for their own benefit.

How does Natural Language Processing (NLP) work?

NLP tools use text vectorization to turn text into a machine-readable format. Machine learning algorithms are then fed training data and predicted outputs (tags) to teach machines to associate a given input with its associated output. Machines utilize statistical analysis techniques to create their own "knowledge bank" and identify which qualities best describe the texts before predicting outcomes for unknown data.

NLP software carries out three primary tasks:
- It starts by dissecting the language (text or voice) into its basic components.
- It then attempts to determine the relationships between these pieces of information.
- Lastly, it tries to explain these relationships.

Each of these operations, of course, involves a great deal more stages. Language proficiency is necessary, as well as expertise in algorithms, statistics, and programming.

What are the applications of Natural Language Processing?

- Sentiment analysis is the use of NLP techniques to extract subjective information from text, often to determine the attitude of a speaker or writer.
- Machine translation involves the use of software to translate text or speech from one language to another.
- Chatbots are AI programs that can conduct conversations with human users through text or voice interfaces, often using NLP.