nikolaydubina/go-ml-benchmarks
⏱ Benchmarks of machine learning inference for Go
This project helps Go service developers quickly understand the performance implications of integrating machine learning inference. It takes a machine learning model (specifically tabular XGBoost) and raw structured data as input. It then measures and compares the speed of different integration methods, outputting detailed benchmarks to guide developers in choosing the fastest approach for their Go backend services.
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Use this if you are developing a Go backend service and need to integrate machine learning inference for structured, single-sample data with the lowest possible latency.
Not ideal if you are working with non-tabular data like images or text, or if your machine learning models are not XGBoost-based.
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Go
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Last pushed
May 09, 2024
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