Tokens are the smallest units of meaning in a text, used in natural language processing to break down and analyze language data. They are essential for tasks like text classification, sentiment analysis, and machine translation, as they help in understanding and manipulating the structure of language.

Tokens

Smallest units of meaning

Natural language processing (NLP) is a field at the intersection of computer science, artificial intelligence, and linguistics, focused on enabling computers to understand, interpret, and generate human language. It encompasses a wide range of applications, from speech recognition and sentiment analysis to machine translation and conversational agents, leveraging techniques like machine learning and deep learning to improve accuracy and efficiency.

Natural Language Processing

Language Data

Text classification is a supervised learning task where the goal is to assign predefined categories to text data based on its content. It is widely used in applications like sentiment analysis, spam detection, and topic categorization, leveraging techniques from natural language processing and machine learning.

Text Classification

Sentiment analysis is a computational technique used to determine the emotional tone behind words in text, providing insights into public sentiment and opinions. It is widely applied in fields such as marketing, customer service, and social media monitoring to gauge consumer attitudes and inform decision-making.

Sentiment Analysis

Machine translation is the process of using artificial intelligence to automatically translate text or speech from one language to another, aiming to preserve meaning and context. It involves complex algorithms and models that leverage linguistic data and neural networks to improve accuracy and fluency over time.

Concepts

Relevant Degrees

Your Lessons