Sathish SKN
@sathishskn4
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Machine Learning Engineer
Afame Technologies •  May 2024 - May 2024•  Remote
During my internship, I led a Spam SMS Detection project. I used machine learning classifiers like Naive Bayes, Logistic Regression, and Support Vector Machine, with word embedding techniques Word2Vec and TF-IDF. The dataset was imbalanced, so I built models using both the original data and balanced data through the SMOTE technique. I compared the models using metrics like Accuracy, Precision, Recall, and F1-score. The Naive Bayes model performed well, achieving an accuracy of 0.978475. The Support Vector Machine model trained on balanced data also performed well, with an accuracy of 0.939013. The comparative analysis revealed that TF-IDF provided superior results compared to Word2Vec. This project is ready for real-world applications and has been a testament to my technical prowess. It has been a rewarding journey, solidifying my expertise in Natural Language Processing and Machine Learning.
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