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Machine Learning
1.4M Dataset Multilingual Sentiment Classifier
Natural language processing pipeline trained on ~1.4 million English and Turkish text samples to classify customer reviews and feedback sentiment.
NLPMachine LearningTF-IDFPythonScikit-Learn
The Problem
Why this matters
Global businesses receive customer feedback in multiple languages, requiring automated sentiment analysis that scales across large text volumes.
Architecture
System Design
Preprocessing pipeline cleaning text noise, applying TF-IDF vectorization, and benchmarking Logistic Regression, Naive Bayes, and SGD classifiers over 1.4 million samples.
Stack
Technologies Used
PythonScikit-LearnTF-IDFPandasNLTK
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