python

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.

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Technology

Python

Language

En

Rating

Chapters

11

Introduction

Import NLTK

Tokenization

Stopwords

List Comprehension

Stemming

Tagging

Lemmatizer

Regexp Tokenizer

Data Visualization

Word Cloud

0%

Introduction

Import NLTK

Tokenization

Stopwords

List Comprehension

Stemming

Tagging

Lemmatizer

Regexp Tokenizer

Data Visualization

Word Cloud

Course description

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.

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