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Text Preprocessing & Embeddings

Learn essential NLP preprocessing techniques and embedding methods used in modern text-based machine...Read More

LevelBeginner

Duration12+ months

LanguageEnglish

Learn essential NLP preprocessing techniques and embedding methods used in modern text-based machine

What You'll Learn

Clean and preprocess raw text for ML and NLP tasks
Apply tokenization, lemmatization, stemming, and normalization
Understand traditional and modern embedding methods
Build vocabulary representations for machine learning models
Use Word2Vec, GloVe, and Transformer-based embeddings

Requirements

Basic Python
familiarity with ML fundamentals
NLTK / spaCy preferred.

Earn Your Certificate

Showcase your skills with a certificate! Complete the course, submit your project, and earn your certificate. Here's a sample of what you'll receive to show off your accomplishments.

Course Curriculum

4 Chapters

21 Lectures

31h 6m 32s

1. Text Cleaning & Normalization

5 Lectures|1 Assignment|1 Quiz|5h 33m

1. Tokenization Techniques (Whitespace, Word, Subword)

2. Text Cleaning: Lowercasing, Noise Removal

3. Introduction to NLP Preprocessing

4. Normalization, Lemmatization & Stemming

5. Stopword Removal & Vocabulary Building

6. Lesson 1 Preprocessing

7. Text Cleaning Notebook

8. Resource — Text Cleaning Reference PDF

2. Vectorization & Classical Embeddings

5 Lectures|1 Assignment|8h 3m

3. Word Embeddings (Word2Vec, GloVe)

5 Lectures|1 Quiz|6h 16m 32s

4. Modern Embeddings (BERT, Transformers)

6 Lectures|11h 14m

Live Classes from the courses

Upcoming

Text Preprocessing & Embeddings