Natural Language Processing(NLP)

Learn Natural Language Processing(NLP) Development

Introduction to Natural Language Processing

Text Preprocessing

Sentiment Analysis

Named Entity Recognition (NER)

Python Full Stack

Introduction to Natural Language Processing

Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and humans through natural language. It enables machines to understand, interpret, and generate human language, facilitating more natural and intuitive communication.

Text Preprocessing

Text preprocessing involves preparing raw text data for analysis by cleaning and transforming it. Common techniques include tokenization, stemming, lemmatization, and removing stop words, which are essential for improving the performance of NLP models.

Sentiment Analysis

Sentiment analysis is the process of determining the emotional tone behind a piece of text. It helps in understanding opinions, attitudes, and emotions expressed in text, commonly used in social media monitoring, customer feedback analysis, and market research.


Named Entity Recognition (NER)

NER is a technique used to identify and classify named entities in text, such as names of people, organizations, locations, dates, and more. It is crucial for extracting meaningful information from text and structuring unstructured data.