alirezadir/Production-Level-Deep-Learning
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
This guide helps machine learning engineers and data scientists successfully launch deep learning models into real-world applications. It outlines a comprehensive process, taking you from raw data sources through model development to deployment and ongoing management. You'll gain practical advice and tool recommendations to overcome common challenges in bringing AI projects to life.
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Use this if you are an ML engineer or data scientist responsible for deploying deep learning models beyond experimental stages and into stable, high-performance production environments.
Not ideal if you are looking for guidance solely on model training techniques or foundational deep learning theory without an emphasis on the complete MLOps lifecycle.
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