go-ml-benchmarks VS go-featureprocessing

Compare go-ml-benchmarks vs go-featureprocessing and see what are their differences.

go-ml-benchmarks

⏱ Benchmarks of machine learning inference for Go (by nikolaydubina)
Machine Learning Benchmarks Xgboost scikit-learn Inference Grpc Go Python CPP
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go-featureprocessing

🔥 Fast, simple sklearn-like feature processing for Go (by nikolaydubina)
Machine Learning Go feature-engineering
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go-ml-benchmarks go-featureprocessing
5 6
30 115
- -
2.7 5.2
11 days ago 11 days ago
Go Go
- MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

go-ml-benchmarks

Posts with mentions or reviews of go-ml-benchmarks. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-05.

go-featureprocessing

Posts with mentions or reviews of go-featureprocessing. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-05.

What are some alternatives?

When comparing go-ml-benchmarks and go-featureprocessing you can also consider the following projects:

leaves - pure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks

m2cgen - Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

tflite-golang-gan-example

bayesian - Naive Bayesian Classification for Golang.

go-bench-stream - 🌊 Go Benchmarks for Stream Processing

gosseract - Go package for OCR (Optical Character Recognition), by using Tesseract C++ library

openmodelz - One-click machine learning deployment (LLM, text-to-image and so on) at scale on any cluster (GCP, AWS, Lambda labs, your home lab, or even a single machine).

ocrserver - A simple OCR API server, seriously easy to be deployed by Docker, on Heroku as well

llama2.go - LLaMA-2 in native Go

gago - :four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)

sklearn - bits of sklearn ported to Go #golang

goml - On-line Machine Learning in Go (and so much more)

go-ml-benchmarks vs leaves go-featureprocessing vs m2cgen go-ml-benchmarks vs tflite-golang-gan-example go-featureprocessing vs bayesian go-ml-benchmarks vs go-bench-stream go-featureprocessing vs gosseract go-ml-benchmarks vs openmodelz go-featureprocessing vs ocrserver go-ml-benchmarks vs llama2.go go-featureprocessing vs gago go-featureprocessing vs sklearn go-featureprocessing vs goml