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Text Preprocessing with Python

Name: Text Preprocessing with Python
Price: 59 USD
Author: Valentine Mwangi

Gain insights into text preprocessing with Python. Explore text cleaning, normalization, and advanced techniques like BoW and TF-IDF. Discover skills to handle unstructured data effectively for NLP.

4.3

60 lessons

2 projects

16h

Created by Valentine Mwangi

What's included

60 lessons across 12 modules
10 quizzes with instant feedback
2 projects in preconfigured environments
AI Tutor on every lesson

Join 3.1 million developers at

What You'll Learn

An understanding of the significance of text preprocessing in natural language processing and its impact on text analysis tasks
Hands-on experience applying various text-cleaning techniques, including the use of regular expressions and lowercase and uppercase transformations
The ability to evaluate the effectiveness of different text normalization techniques
Familiarity with designing and implementing different text representation models, such as bag-of-words and TF-IDF
Hands-on experience applying various text preprocessing techniques and models in a real-world application

Learning Roadmap

60 Lessons1 Project10 Quizzes26 Challenges

About This Course

Get familiar with the importance and techniques of text preprocessing for effective NLP.

Course Introduction

Introduction To Text Preprocessing

Look at text preprocessing techniques, data types, and processing stages for better analysis.

Overview of Text Preprocessing and Its Importance

Types of Text Data and Its Characteristics

The Stages of Text Preprocessing

Quiz: Introduction to Text Preprocessing

Regular Expressions

6 Lessons

Go hands-on with regular expressions to identify patterns, preprocess, and extract text data.

Irrelevant Text Data

7 Lessons

Break down the steps to effectively manage, clean, and preprocess irrelevant text data.

Basic Text Preprocessing Techniques

6 Lessons

Dig deeper into text preprocessing techniques like lowercasing, punctuation removal, and handling special characters.

Indexing

6 Lessons

Focus on efficient text processing through various indexing methods and implementing code challenges.

Text Transformation

6 Lessons

Piece together the parts of text tokenization, normalization, stemming, lemmatization, and transformation challenges.

Text Representation

6 Lessons

Learn how to use text representation techniques like BoW, TF-IDF, and word embeddings.

Text Feature Engineering

6 Lessons

Unpack the core of text feature construction, scaling, date handling, and coding challenges.

10.

Advanced Text Preprocessing

6 Lessons

Go hands-on with part-of-speech tagging, named entity recognition, and text classification.

11.

N-grams

5 Lessons

Grasp the fundamentals of N-grams, their applications in text classification, and practical code challenges.

Text Classification of Customer Reviews

Project

12.

Conclusion

Consolidate your skills in essential text preprocessing techniques for advanced NLP tasks.

Course Summary

Text Classification Using PyTorch

Project

Premium

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

About this course

WHY I WROTE THIS COURSE

This course is designed to empower you with essential skills for effectively handling text data in the context of natural language processing (NLP). You’ll embark on a transformative journey that will equip you with a solid foundation in text manipulation, enabling you to tackle the challenges of unstructured data. The course discusses both fundamental and advanced text preprocessing techniques. You’ll learn how to clean text and remove noise, irrelevant characters, and inconsistencies in text data. Once the data is ready for analysis, you’ll learn text normalization techniques such as stemming, lemmatization, and casing. In addition to mastering preprocessing fundamentals, you’ll also learn techniques such as bag-of-words (BoW) and term frequency-inverse document frequency (TF-IDF). By the end of the course, you’ll be able to position yourself for success in a data-centric world where the ability to extract meaning from unstructured textual information is a prized skill.

ABOUT THE AUTHOR

Valentine Mwangi

Highly Experienced Educator and Data Scientist Empowering Thousands of Students Worldwide with Cutting-Edge Data Science Education and Interactive Workshops.

Learn more about Valentine

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