Machine Learning with Go
A short tour through ML libraries in Go, golab 2018.
About ten self-contained examples.
Overview
- (1) data acquisition and preparation (csv, xml, json, dataframe)
- (2) linear regression example (regression)
- (3) naive bayes spam classifier (bayesian)
- (4) logistic regression (goml)
- (5) a decision tree classifier (golearn)
- (6) k-nearest neighbors (golearn)
- (7) a simple neural network (gophernet, gonum)
- (8) pre-trained model (tensorflow/go)
Note: This is an ongoing exploration and there are a few interesting libraries that I intend to include in the future:
- tfgo, which solves a few issues with tensorflow
- gorgonia, a generic machine learning library, which has been used for an AlphaZero implementation.
The initial version of the workshop traded overview for interactivity, which made it less interesting as it could have been.
Ombrelli bianchi sospesi in aria tra i palazzi di via Romana, a Firenze (Foto Cge Fotogiornalismo), (Source).