goRecommend alternatives and similar packages
Based on the "Machine Learning" category.
Alternatively, view goRecommend alternatives based on common mentions on social networks and blogs.
-
tfgo
Easy to use Tensorflow bindings: simplifies the usage of the official Tensorflow Go bindings. Define computational graphs in Go, load and execute models trained in Python. -
CloudForest
Fast, flexible, multi-threaded ensembles of decision trees for machine learning in pure Go. -
Goptuna
Bayesian optimization framework for black-box functions written in Go. Everything will be optimized. -
go-featureprocessing
Fast and convenient feature processing for low latency machine leraning in Go.
Get performance insights in less than 4 minutes
Do you think we are missing an alternative of goRecommend or a related project?
README
Go Recommend
Recommendation algorithms (Collaborative Filtering) in Go!
Background
Collaborative Filtering (CF) is oftentimes used for item recommendations for users, and many libraries exist for other languages (popular implementations include Mahout, Prediction.IO, Apache MLLib ALS etc..). As there are very few machine learning packages out there for Go, I decided to put together some model based CF algorithms that I thought were interesting.
Collaborative Filters inside this package. See each folder for examples/specifications
- Alternating Least Squares (more info here ) for both the Implicit and Explicit Case
- Tests now complete
- Use the implicit case for a confidence rating; explicit for predicting ratings
- Simple Bayesian Collaborative Filtering Algorithm, see details here
- Tests complete
- Similarity/Memory-based (using correlation, cosine and jaccard similarity) based CF, which incorporates a nearest neighbor type metric can be found in the CF folder.
- Tests complete
- See README for more details
- Todo: consider approximate nearest neighbors algorithm.
Most of the recommendation algorithms in this package are briefly outlined in this article
Additional
- If you have any questions/comments, please feel free to reach me at tim [dot] kaye [at] lytics [dot] io