Shypd.aiThe largest open index of AI toolsDeep-Learning-in-Production is an open-source GitHub repository providing notes and references for deploying deep learning models into production. It offers resources for converting PyTorch, TensorFlow, and Keras models, and integrating them with various deployment tools and frameworks.
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Deep-Learning-in-Production is a comprehensive GitHub repository curated by ahkarami, designed to serve as a valuable resource for deploying deep learning-based models in production environments. The repository compiles useful notes and references across various deep learning frameworks, including PyTorch, TensorFlow, Keras, and MXNet. It covers essential topics such as model conversion (e.g., PyTorch to C++, Keras to C++), model serving with tools like Flask, TorchServe, and TensorFlow Serving, and deployment on platforms like AWS Lambda and Kubernetes. Additionally, it provides insights into model quantization, speed optimization, and general deep learning deployment toolkits like OpenVINO and NVIDIA Triton Inference Server. The repository also includes resources for front-end and back-end development, mobile/embedded device deployment, and MLOps, making it a holistic guide for machine learning engineers and data scientists looking to operationalize their models.
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