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Source channel @githubtrending · Post #15239 · Oct 21

#python#artificial_intelligence#cloud_ml#computer_systems#courseware#deep_learning#edge_machine_learning#embedded_ml#machine_learning#machine_learning_systems#mobile_ml#textbook#tinyml You can learn how to build real-world AI systems from start to finish with an open-source textbook originally from Harvard University. It teaches you not just how to train AI models but how to design scalable systems, manage data pipelines, deploy models in production, monitor them continuously, and optimize for devices like phones or IoT gadgets. This helps you become an engineer who can create efficient, reliable, and sustainable AI systems that work well in practice. The book offers hands-on labs, community support, and free online access, making it easier to gain practical skills in machine learning systems engineering. https://github.com/harvard-edge/cs249r_book

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@githubtrending · Post #15271 · 11/05/2025, 12:30 PM

#cplusplus#arm#baidu#deep_learning#embedded#fpga#mali#mdl#mobile#mobile_deep_learning#neural_network Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance. https://github.com/PaddlePaddle/Paddle-Lite