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A heterogeneous ML ensemble (RF, GB, Multi Output DNN, Confidence Scorer) and LLaMA 3.3 engine transforming career paralysis into constraint-aware, probabilistic life path simulations.
A modular ML ensemble and LLaMA 3.3 reasoning layer providing constraint-aware, probabilistic risk analysis to guide grads through high-stakes life forks.
A heterogeneous ML ensemble (RF, GB, DNN, Confidence Scorer) and LLaMA 3.3 engine transforming career paralysis into constraint-aware, probabilistic life path simulations.
Almost all other hackathon medical AI applications are just LLMs dressed up as chatbots. However, our project RedFlag uses the CNN that was pre-trained on the clinical microscopy dataset from Kaggle.
Explainable computer vision for rapid anemia screening. Triaging blood smear microscopy images in under a second with 96.3% sensitivity using MobileNetV2 and Grad-CAM heatmaps.
