Identifying the Most Frequent Words in Text
Curso
265 Alunos já inscritos- Grasp the essentials of handling human language data with the Natural Language Toolkit (NLTK).
- Gain proficiency in text processing through tokenization, stemming, tagging, and parsing techniques.
- Harness the power of list comprehensiveness to streamline text analysis tasks.
- Learn to enhance data visualization by creating telling word clouds.
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Existem 1 módulos neste 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.- IntroductionPré-visualização
- Import NLTKPré-visualização
- TokenizationPré-visualização
- StopwordsPré-visualização
- List ComprehensionPré-visualização
- StemmingPré-visualização
- TaggingPré-visualização
- LemmatizerPré-visualização
- Regexp TokenizerPré-visualização
- Data VisualizationPré-visualização
- Word CloudPré-visualização
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Kwizera Mugisha
The teaching methodology at Codefinity is excellent, and I particularly appreciate how it has prepared me to handle real-world coding problems. Currently, I am delving into Node.js and eagerly anticipate building full-stack projects that integrate all the knowledge I have gained.

Sherry Barnes-Fox
My first course was 4 hours, I did it in a few days, "nugget-style. The instructions are very clear and easy to understand. There is even a hint to help you get the answer, and if you still cannot get the answer, then you can display the answer. I love the learning style that is used, it engages me.

Bill Wagner
I have really liked the browser-based lessons that allow me to code within the lesson. The RUN button allows me to test the code I write before submitting for a grade.

Stephanie Chan
As I went through the first course of the Python track, I liked the way the course was lay out (in easy and digestible modules) with little exercises at the end of each concept.

Daniel Chinea
I have gained a lot of practical and logical thinking skills, along with patience for myself and confidence in myself that I can learn programming.

Steve Bruening
The learning was progressive and made it easy to follow along and make progress. I could feel my skills increasing and building on each other as the course went along.
Avaliações de alunos
3.8
4 avaliações
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4
75%
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Mostrando 3 de 4 avaliações
Wassim Mefteh
4
Avaliado em Nov 5, 2024
Jared Pechauer
3
Avaliado em Mar 23, 2024
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
4
Avaliado em Jan 24, 2024
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.
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