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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
Start with the NLP Roadmap View GitHub Repository

Feature Extraction in NLP - From Clean Text to Count-Based Features

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NLP by Vinod - Foundations Feature Extraction Feature Extraction in NLP - From Clean Text to Count-Based Features. After text preprocessing, I learned how cleaned words are converted into numbers using word count, frequency distribution, one-hot encoding, Bag of Words, n-grams and TF-IDF. NLP Feature Extraction Bag of Words TF-IDF
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