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Showing posts with the label Feature Extraction
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.
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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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Text Preprocessing in NLP - Cleaning Raw Text Before Feature Extraction

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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
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