Identifying the Most Frequent Words in Text
Edoardo Cantagallo
Python
11 Chapters
0 Studying now
In this project, we will be utilizing the capabilities of the Natural Language Toolkit (NLTK), a versatile and comprehensive library in Python designed for working with human language data. Our focus will encompass several core areas of natural language processing: tokenization, stemming, tagging and parsing. These NLTK features will form the backbone of our text processing and analysis tasks, making it an essential tool in our project for handling and extracting meaningful insights from language data.
Tecnologia
Python
Língua
En
Avaliação
2.6
Capítulos
11
Descrição do Curso
In this project, we will be utilizing the capabilities of the Natural Language Toolkit (NLTK), a versatile and comprehensive library in Python designed for working with human language data. Our focus will encompass several core areas of natural language processing: tokenization, stemming, tagging and parsing. These NLTK features will form the backbone of our text processing and analysis tasks, making it an essential tool in our project for handling and extracting meaningful insights from language data.
Críticas
8 avaliações
Jared P.
dias atrás
Like others said, this is an interesting topic. I think this course really just shows you some methods that are available but doesn't really challenge you to learn them. Its more of a exploration than a lesson.
Jenna W.
dias atrás
Interesting lesson. However, the content is more medium than beginner. Many of the hints provided were confusing and I needed to reference the solutions to move on. Overall, very informative and well done.
Jordan F.
dias atrás
Good Lesson but seems a bit too complex for beginner...
D H.
dias atrás
no explanation on how to do things...
Anne H.
dias atrás
Really disappointing. It doesn't really teach anything, it doesn't accurately tell you the names of functions to use, just what they do, this would be an opportunity to teach use of documentation to check these details. Even when it gives the names, there are basic errors like NLTK when it's case sensitive and nltk not NLTK. Additionally, when I have gone through this, there is an error in the package, so although all my code passed the tests, it didn't actually work because of an error beyond my control.
Олександр К.
dias atrás
по-суті, частково повторює більш цікавий і ефективний курс "Знайомство з НЛП"....
Max S.
dias atrás
A good 3/4 of what is being explained about the project is lacking....
