This is project, developed a deep learning model using Tensorflow and CNNs to classify images into multi animal categories with high accuracy. Preprocessed image data, optimized model architecture and achieved effective generalization on unseen data.
This project aims to build and evaluate machine learning models to predict heart failure based on patient data. The project includes the implementation of 6 machine learning algorithms.
AI-powered plant disease detection system using CNN deep learning. Identifies 38+ crop diseases from leaf images with high accuracy. Built with TensorFlow/Keras and Streamlit for real-time agricultural diagnostics.
Brain Tumor Classification
This repository is to experiment the integration with @ggml-org/whisper.cpp for offline STT + pyannote/speaker-diarization-3.1
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