Benchmarking of MultiClass Classification models
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Updated
Dec 8, 2022 - Python
Benchmarking of MultiClass Classification models
High-dimensional NLP pipeline for imbalanced comment classification using TF-IDF, feature engineering, and LightGBM (Macro F1: 0.8344)
Automated classification of 7 different types of dry beans using machine learning techniques. This project leverages computer vision-extracted geometric and shape features (such as Area, Perimeter, and Shape Factors) to accurately identify bean varieties including Barbunya, Bombay, Cali, Dermason, Horoz, Seker, and Sira.
Academic Machine Learning (6 months) Sessional Project
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