Natural Language Processing Essentials

Text processing basics in Python: string manipulation, regular expressions, and text preprocessing techniques.

1. 1Python Text Basics Part 1Free
2. 2Python Text Basics Part 2
3. 3Python Text Basics Part 3
4. 4Python Text Basics Part 4
5. 5Python Text Basics Part 5
6. 6Python Text Basics Part 6

NLP foundations: tokenization, stemming, lemmatization, stopword removal, and bag of words representation.

1. 1NLP Basics Part 1Free
2. 2NLP Basics Part 2
3. 3NLP Basics Part 3
4. 4NLP Basics Part 4
5. 5NLP Basics Part 5
6. 6NLP Basics Part 6

POS tagging and NER: understanding language structure, automatically identifying entities (names, locations, organizations) in text.

1. 1Part of Speech and Named Entity Recognition Part 1Free
2. 2Part of Speech and Named Entity Recognition Part 2
3. 3Part of Speech and Named Entity Recognition Part 3
4. 4Part of Speech and Named Entity Recognition Part 4
5. 5Part of Speech and Named Entity Recognition Part 5
6. 6Part of Speech and Named Entity Recognition Part 6

Text classification: TF-IDF, feature extraction from text, and building text classification models using ML.

1. 1Text Classification Part 1Free
2. 2Text Classification Part 2
3. 3Text Classification Part 3
4. 4Text Classification Part 4
5. 5Text Classification Part 5
6. 6Text Classification Part 6

Exercises and NLP portfolio project: build an end-to-end text classification system from preprocessing to model deployment.

1. 1Exercise & Project Portfolio 11 – Text ClassificationFree