doongz/mlc-ai
机器学习编译 陈天奇
This course helps machine learning engineers and system programmers optimize deep learning models for faster deployment on various hardware. It teaches how to transform models developed in frameworks like TensorFlow or PyTorch into high-performance, hardware-adapted 'deployment mode' code. You'll learn to use tools like Apache TVM to take a model and output optimized, deployable code, making your models run more efficiently in real-world applications.
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Use this if you are a machine learning engineer or system programmer who needs to deploy models efficiently across different hardware platforms and want to understand the underlying compilation processes.
Not ideal if you are looking for a beginner-level introduction to deep learning or only use high-level machine learning frameworks without needing to optimize deployment.
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Jan 01, 2023
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