@ -118,6 +118,7 @@ Please take a quick gander at the [contribution guidelines](https://github.com/a
*Databases implemented in Go.*
* [bolt](https://github.com/boltdb/bolt) - A low-level key/value database for Go.
* [cache2go](https://github.com/muesli/cache2go) - An in-memory key:value cache which supports automatic invalidation based on timeouts.
* [diskv](https://github.com/peterbourgon/diskv) - A home-grown disk-backed key-value store.
* [go-cache](https://github.com/pmylund/go-cache) - An in-memory key:value store/cache (similar to Memcached) library for Go, suitable for single-machine applications.
* [goleveldb](https://github.com/syndtr/goleveldb) - An implementation of the [LevelDB](https://code.google.com/p/leveldb/) key/value database in the Go.
@ -247,6 +248,7 @@ Please take a quick gander at the [contribution guidelines](https://github.com/a
* [imaging](https://github.com/disintegration/imaging) - Simple Go image processing package.
* [resize](https://github.com/nfnt/resize) - Image resizing for the Go with common interpolation methods.
* [rez](https://github.com/bamiaux/rez) - Image resizing in pure Go and SIMD.
* [smartcrop](https://github.com/muesli/smartcrop) - Finds good crops for arbitrary images and crop sizes
* [svgo](https://github.com/ajstarks/svgo) - Go Language Library for SVG generation.
@ -281,6 +283,7 @@ Please take a quick gander at the [contribution guidelines](https://github.com/a
* [mlgo](https://code.google.com/p/mlgo/) - This project aims to provide minimalistic machine learning algorithms in Go.
* [neural-go](https://github.com/schuyler/neural-go) - A multilayer perceptron network implemented in Go, with training via backpropagation.
* [probab](https://code.google.com/p/probab/) - Probability distribution functions. Bayesian inference. Written in pure Go.
Christian Muehlhaeuser
10 years ago