ahkarami/Deep-Learning-in-Production
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
This resource collects essential guides and references for putting deep learning models, particularly those built with PyTorch, TensorFlow, or Keras, into active use. It provides practical information on how to transform trained models into systems that can process new data and deliver predictions or insights. Machine learning engineers and MLOps professionals will find this useful for operationalizing AI models.
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Use this if you need practical guidance and resources to move your developed deep learning models from an experimental stage to a reliable, production-ready system that can handle real-world requests.
Not ideal if you are looking for an off-the-shelf tool or a code library that automatically deploys models without requiring any understanding of the underlying processes.
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