Multiclass Classification with Multiple Models

● Implemented a variety of machine learning models (CNN, RNN, ANN, LSTM, BiLSTM) to tackle complex multiclass classification challenges in an eight-class cancer dataset. Achieved an average classification accuracy of 90% across all models, showcasing proficiency in model selection and development.

● Orchestrated collaboration with faculty to conceptualize, develop, and evaluate advanced machine learning models, culminating in comprehensive classification reports that led to a 20% increase in accuracy metrics.