This repository is a comprehensive collection of TensorFlow Lite example applications for on-device machine learning, covering tasks such as image classification, object detection, pose estimation, audio classification, BERT question answering, gesture recognition, and more. It provides complete Android (Kotlin/Java), iOS (Swift), Raspberry Pi, and web implementations, each demonstrating best practices for camera integration, hardware delegate selection, and real-time inference. Additionally, the repository includes the TensorFlow Lite Model Maker library, which offers high-level APIs for training and exporting custom TFLite models from user data, along with research/educational models (DenseNet, pix2pix, NMT). While the codebase shows some duplication across platforms and occasional legacy API usage, it remains a valuable reference for developers building edge ML applications.