Data Science Industrial Program - Text Classifier Builder
I built and validated supervised text classifiers for hate speech and spam detection using Scikit-learn. My tasks involved text preprocessing, feature engineering, and training models to accurately categorize textual data. I utilized various natural language processing techniques to optimize the performance and reliability of classifiers. • Conducted text data preprocessing, including stemming and stop-word removal. • Engineered text features using TF-IDF and CountVectorizer. • Trained and evaluated classification models, achieving high accuracy. • Applied exploratory data analysis to understand and impute missing dataset values.