Identifying the Most Frequent Words in Text

Edoardo Cantagallo

3.8

Python

11 Chapters

1 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.

Identifying the Most Frequent Words in Text

BEGINNER

3.8

#python

Author: Edoardo Cantagallo

Course description

Ratings & reviews

3.8 (4)

3.8out of 5

75%

25%

4 ratings

Jared P.

431 days ago

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. Show more

Jenna W.

490 days ago

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. Show more

Jordan F.

525 days ago

Good Lesson but seems a bit too complex for beginner...

Introduction

Import NLTK

Tokenization

Stopwords

List Comprehension

Stemming

Tagging

Lemmatizer

Regexp Tokenizer

Data Visualization

Word Cloud

Complete all chapters to get certificate

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.