Natural Language Processing (NLP) is a fascinating field that focuses on the interaction between computers and human language. In this section, we will explore various tutorials on NLP research topics.
Topics Covered
- Basic Concepts of NLP
- Text Classification
- Sentiment Analysis
- Machine Translation
- Named Entity Recognition
Basic Concepts of NLP
Natural Language Processing is the field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human (natural) languages. As such, NLP is related to the area of human-computer interaction.
To learn more about NLP basics, you can visit our NLP Basics Tutorial.
Text Classification
Text classification is a common task in NLP where the goal is to categorize text into predefined categories. This is a fundamental task in various applications, such as spam detection, sentiment analysis, and topic classification.
For more information on text classification, check out our Text Classification Tutorial.
Sentiment Analysis
Sentiment analysis is the process of determining whether a piece of text is positive, negative, or neutral. It is widely used in social media monitoring, customer feedback analysis, and market research.
To dive deeper into sentiment analysis, refer to our Sentiment Analysis Tutorial.
Machine Translation
Machine translation is the process of automatically translating text from one language to another. It has become an essential tool for communication and globalization.
For more details on machine translation, explore our Machine Translation Tutorial.
Named Entity Recognition
Named Entity Recognition (NER) is the process of identifying and classifying named entities in text into predefined categories such as person names, organizations, locations, and more.
Learn more about NER in our Named Entity Recognition Tutorial.
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