Deep-Learning-in-Production

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

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Convert PyTorch Models in Production:

Convert PyTorch Models to C++:

Deploy TensorFlow Models in Production:

Convert Keras Models in Production:

Deploy MXNet Models in Production:

Deploy Machine Learning Models with Go:

General Deep Learning Deployment Toolkits:

Huawei Deep Learning Framework:

General Deep Learning Compiler Stack:

Model Conversion between Deep Learning Frameworks:

Some Caffe2 Tutorials:

Some Useful Resources for Designing UI (Front-End Development):

Mobile & Embedded Devices Development:

Back-End Development Part:

GPU Management Libraries:

Speed-up & Scalabale Python Codes:

Hardware Notes for Deep Learning:

Other:

Deep Learning In Production

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

Deep Learning In Production Info

โญ Stars3139
๐Ÿ”— Source Codegithub.com
๐Ÿ•’ Last Update8 months ago
๐Ÿ•’ Created4 years ago
๐Ÿž Open Issues4
โž— Star-Issue Ratio785
๐Ÿ˜Ž Authorahkarami