A custom implementation of a Denoising Diffusion Probabilistic Model (DDPM) in PyTorch, trained on the Oxford Flowers 102 dataset to generate synthetic images.
Vision–language classification on the Oxford Flowers dataset using CLIP, exploring zero-shot inference and feature-extraction fine-tuning.
🌸 Complete Udacity ML TensorFlow Image Classifier Project - Flower species classification using MobileNetV2 transfer learning with 102 Oxford flower classes. Enhanced with automated conda setup, cross-platform GPU detection, and Apple Silicon support. Achieves 80%+ accuracy.
🌸 Generate synthetic images of flowers using a custom Denoising Diffusion Probabilistic Model (DDPM) implemented in PyTorch.
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