Build an NLP Text Classification Pipeline with ML AlgorithmsBuild an NLP Text Classification Pipeline with ML Algorithms
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Mani Sharan's avatar
Mani Sharan Bommakanti
• 2d
Built an end-to-end NLP pipeline to classify text reviews as Positive, Negative, or Neutral. Used NLTK for tokenization and lemmatization, TF-IDF for vectorization, and trained 3 ML classifiers — Logistic Regression, Naive Bayes, and SVM. Visualized sentiment trends and model accuracy using Matplotlib and Seaborn.
Data AnalysisData EngineeringPythonscikit-learnMachine Learning EngineeringNLTK
Marco's avatar
Marco Mastroeni
• 1d
Very interesting :) I personally believe that this type of implementation have a huge future ahead, since this type of technology can effectively predict the trends and the sentiments of the crowd toward something. If someone finds the way to exploit this in a shop or a...
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