dataframe-go
randomforest
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| dataframe-go | randomforest | |
|---|---|---|
| 3 | 2 | |
| 1,112 | 39 | |
| 2.6% | - | |
| 0.0 | 2.6 | |
| about 2 years ago | about 2 months ago | |
| Go | Go | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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dataframe-go
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packages similar to Pandas
Numpy functionality is largely covered by https://www.gonum.org/ but for pandas I'm not sure if there is an equivalent as widely accepted. However, you might try https://github.com/rocketlaunchr/dataframe-go which I have not tried but it looks like it covers some of what you're looking for
- Machine Learning
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Dynamic Structs
For guidance on how to use it: https://github.com/rocketlaunchr/dataframe-go/blob/master/exports/parquet.go
randomforest
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Machine Learning
I did end up writing and using a custom library for Random Forest (it's also in AwesomGo) in one real-world project (detecting Alzheimer's and Parkinson's from speech from a mobile app) - https://github.com/malaschitz/randomForest I had better results than the team who used TensorFlow and most importantly I didn't have to use any other technology than Go. For NN's it's probably best to use https://gorgonia.org/ - but it's not exactly a user friendly library. But there is a whole book on it - Hands-On Deep Learning with Go.
- Boruta algorithm added to Random Forest library
What are some alternatives?
gonum - Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more
GoLearn - Machine Learning for Go
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
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
qframe - Immutable data frame for Go
sklearn - bits of sklearn ported to Go #golang
gonum/plot - A repository for plotting and visualizing data
goml - On-line Machine Learning in Go (and so much more)
Stats - A well tested and comprehensive Golang statistics library package with no dependencies.
onnx-go - onnx-go gives the ability to import a pre-trained neural network within Go without being linked to a framework or library.
gonum/mat64
EAGO