Posts

Showing posts with the label NLTK
NLP by Vinod

A structured public journey from NLP fundamentals to real-world AI systems.

Vinod Codes is where I document my learning in AI, Machine Learning, Deep Learning, Natural Language Processing, Generative AI, and practical projects.

The main series here is NLP by Vinod — a learner-builder journey where I explain concepts with intuition, Python examples, mistakes, GitHub work, and honest implementation notes.

Start here: follow the Foundations Track first, then move into deep learning, transformers, projects, and real-world NLP systems.
NLP Foundations Python for NLP Machine Learning Deep Learning Real Projects

NLP Libraries - NLTK, spaCy, TextBlob and Stanza in Practice

Image
NLP by Vinod - Foundations NLP Libraries NLP Libraries - NLTK, spaCy, TextBlob and Stanza in Practice. After embeddings, I explored the practical NLP libraries that help with tokenization, POS tagging, NER, sentiment analysis, parsing, multilingual processing and quick NLP experiments. NLTK spaCy TextBlob Stanza

Text Preprocessing in NLP - Cleaning Raw Text Before Feature Extraction

Image
NLP by Vinod - Foundations Text Preprocessing Text Preprocessing in NLP - Cleaning Raw Text Before Feature Extraction. After data acquisition, I learned how raw text is cleaned, normalized, tokenized, and prepared before feature extraction. This post connects basic and advanced preprocessing from my notebooks into one clear sequence. NLP Text Cleaning Tokenization Stemming

NLP Learning Roadmap — From Fundamentals to Real-World AI Systems

Image
NLP Learning Roadmap — From Fundamentals to Real-World AI Systems NLP by Vinod • Foundations NLP Learning Roadmap NLP Learning Roadmap: My Structured Plan from Basics to Real AI Systems. A practical Natural Language Processing roadmap covering Python text processing, machine learning, deep learning, transformers, BERT, NLP projects, and deployment. NLP Machine Learning Deep Learning Python Roadmap