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Machine Learning With Go

You're reading from  Machine Learning With Go

Product type Book
Published in Sep 2017
Publisher Packt
ISBN-13 9781785882104
Pages 304 pages
Edition 1st Edition
Languages

Table of Contents (11) Chapters

Preface 1. Gathering and Organizing Data 2. Matrices, Probability, and Statistics 3. Evaluation and Validation 4. Regression 5. Classification 6. Clustering 7. Time Series and Anomaly Detection 8. Neural Networks and Deep Learning 9. Deploying and Distributing Analyses and Models 10. Algorithms/Techniques Related to Machine Learning

References

CSV data:

  • encoding/csv docs: https://golang.org/pkg/encoding/csv/
  • github.com/kniren/gota/dataframe docs: https://godoc.org/github.com/kniren/gota/dataframe

JSON data:

  • encoding/json docs: https://golang.org/pkg/encoding/json/
  • Bill Kennedy's blog post of JSON decoding: https://www.goinggo.net/2014/01/decode-json-documents-in-go.html
  • Ben Johnson's blog post Go Walkthrough: encoding/json package: https://medium.com/go-walkthrough/go-walkthrough-encoding-json-package-9681d1d37a8f

Caching:

  • github.com/patrickmn/go-cache docs: https://godoc.org/github.com/patrickmn/go-cache
  • github.com/boltdb/bolt docs: https://godoc.org/github.com/boltdb/bolt
  • Information about and motivation for BoltDB: https://npf.io/2014/07/intro-to-boltdb-painless-performant-persistence/

Pachyderm:

  • General documentation: http://docs.pachyderm.io
  • Go client docs: https://godoc.org/github.com/pachyderm/pachyderm/src/client
  • Public users Slack team registration: http://docs.pachyderm.io

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Machine Learning With Go
Published in: Sep 2017 Publisher: Packt ISBN-13: 9781785882104
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