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About This Course

Course Introduction

Introduction To Text Preprocessing

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

Basics of Regular Expressions Regular Expressions for Text Preprocessing Advanced Regular Expressions for Text Preprocessing Code Challenges on Regular Expressions Solution Explanations: Regular Expressions Quiz: Regular Expressions

Irrelevant Text Data

Types of Irrelevant Text Data Handling Misspellings Challenges Best Practices Code Challenges on Irrelevant Text Data Solution Explanations: Irrelevant Text Data Quiz: Irrelevant Text Data

Basic Text Preprocessing Techniques

Lowercasing and Uppercasing Text Punctuation Removal Handling Special Characters Code Challenges on Basic Text Preprocessing Techniques Solution Explanations: Basic Preprocessing Techniques Quiz: Basic Text Preprocessing Techniques

Indexing

Overview of Indexing in Text Preprocessing Term-Based and Document-Based Indexing Inverted and Positional Indexing Code Challenges on Indexing Solution Explanations: Indexing Quiz: Indexing

Text Transformation

Text Tokenization Text Normalization Stemming and Lemmatization Code Challenges on Text Transformation Solution Explanations: Text Transformation Quiz: Text Transformation

Text Representation

Bag-of-Words Term Frequency-Inverse Document Frequency Word Embeddings Code Challenges on Text Representation Solution Explanations: Text Representation Quiz: Text Representation

Text Feature Engineering

Feature Construction Feature Scaling Working with Dates Code Challenges on Text Feature Engineering Solution Explanations: Text Feature Engineering Quiz: Text Feature Engineering

Advanced Text Preprocessing

Part-of-Speech Tagging

Named Entity Recognition

Text Classification

Code Challenges on Advanced Text Preprocessing

Solution Explanations: Advanced Text Preprocessing

Quiz: Advanced Text Preprocessing

N-grams

Introduction to N-Grams N-Grams for Text Classification Code Challenges on N-Grams Solution Explanations: N-Grams Quiz: N-Grams

Mini Project

Text Classification of Customer Reviews

Conclusion

Project

Text Classification Using PyTorch

Text Preprocessing with Python/

Text Classification of Customer Reviews

Text Classification of Customer Reviews

Online e-commerce platforms collect lots of data about the products they sell. By performing text classification, these platforms gain insights into customer satisfaction and identify improvement areas in the shopping experience.

In this project, we aim to create a machine-learning model to predict the satisfaction rating of a purchased product. We’ll prepare customer review text data using various text preprocessing tools and techniques and then use it to train the classifier.