Natural Language Processing (NLP)
About Natural Language Processing (NLP)
An interdisciplinary topic within linguistics, computer science, and artificial intelligence called "natural language processing" studies how computers and human language interact, with a focus on how to design computers to process and analyze massive volumes of natural language data. Researchers can better patient care, research endeavors, and illness detection by sifting through unstructured data using natural language processing technologies.
Why is Natural Language Processing (NLP) important?
Scaling other language-related tasks, natural language processing enables computers to converse with people in their own language. For instance, NLP enables computers to read text, hear a voice, analyze it, gauge the mood, and identify the key points.
Who should take the Natural Language Processing (NLP) Exam?
- Anyone who wants to get familiar with Natural Language Processing.
- Data scientist
Natural Language Processing (NLP) Certification Course Outline
- Introduction to Natural Language Processing
- Frequency Distribution
- Conditional Frequency Distribution
- Python for Data Science
- Understanding Regular Expression
- Implementing Regular Expression in Python
- NLP - Text Processing
- Tokenization and Text Normalization
- Exploring Text Data
- Part of Speech Tagging and Grammar Parsing
- Implementing Text Pre-processing Using NLTK
- Build a Basic ML Model for Text Classification