Natural Language Processing for Text Summarization is a natural language processing course for summarizing texts and articles published by Udemy Academy. In this course, you will be introduced to the basic theories of natural language processing and artificial intelligence, and then you will develop three different algorithms for summarizing and extracting abstracts from articles.
Natural language processing is a subset of artificial intelligence, and the goal of the developers is to develop systems that enable computers to read, understand, and analyze human language. Natural language processing helps computers analyze human language in a variety of formats, such as written and audio formats, and provide appropriate answers.
Among the most important applications of natural language processing are translating different languages into each other, converting text to machine audio files and vice versa, building automatic chat robots and voice assistants, automatic question and answer systems, creating descriptions and summaries for images and videos Various, automatic creation of subtitles for videos and video files, analysis of the tone of an audio or text file and recognition of user emotions, summarizing scientific articles and… mentioned.
What you will learn in the Natural Language Processing for Text Summarization course:
- Understand the theory and calculations of algorithms for summarizing texts and articles
- Build various summary algorithms using the Python programming language
- Work with Sumy, by summarization and BERT summarizer libraries
- Summarize articles on web pages and magazines
- Work with NLTK and spaCy libraries to implement natural language processing systems
- Lan algorithm or Lan formula
Instructor: Jones Granatyr and IA Expert Academy
Education Level: Basic
Number of Courses: 43
Duration: 4 hours and 55 minutes
Course topics on 2022/2
Prerequisites for Natural Language Processing for Text Summarization
Basic Python programming
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