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- Machine Learning With Go. Implement Regression, Classification, Clustering, Time-series Models, Neural Networks, and More using the Go Programming Language
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Machine Learning With Go. Implement Regression, Classification, Clustering, Time-series Models, Neural Networks, and More using the Go Programming Language
Ebook
The mission of this book is to turn readers into productive, innovative data analysts who leverage Go to build robust and valuable applications. To this end, the book clearly introduces the technical aspects of building predictive models in Go, but it also helps the reader understand how machine learning workflows are being applied in real-world scenarios.
Machine Learning with Go shows readers how to be productive in machine learning while also producing applications that maintain a high level of integrity. It also gives readers patterns to overcome challenges that are often encountered when trying to integrate machine learning in an engineering organization.
The readers will begin by gaining a solid understanding of how to gather, organize, and parse real-work data from a variety of sources. Readers will then develop a solid statistical toolkit that will allow them to quickly understand gain intuition about the content of a dataset. Finally, the readers will gain hands-on experience implementing essential machine learning techniques (regression, classification, clustering, and so on) with the relevant Go packages.
Finally, the reader will have a solid machine learning mindset and a powerful Go toolkit of techniques, packages, and example implementations.
Machine Learning with Go shows readers how to be productive in machine learning while also producing applications that maintain a high level of integrity. It also gives readers patterns to overcome challenges that are often encountered when trying to integrate machine learning in an engineering organization.
The readers will begin by gaining a solid understanding of how to gather, organize, and parse real-work data from a variety of sources. Readers will then develop a solid statistical toolkit that will allow them to quickly understand gain intuition about the content of a dataset. Finally, the readers will gain hands-on experience implementing essential machine learning techniques (regression, classification, clustering, and so on) with the relevant Go packages.
Finally, the reader will have a solid machine learning mindset and a powerful Go toolkit of techniques, packages, and example implementations.
- 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. Appendix: Algorithms/Techniques Related to ML
- Title: Machine Learning With Go. Implement Regression, Classification, Clustering, Time-series Models, Neural Networks, and More using the Go Programming Language
- Author: Daniel Whitenack
- Original title: Machine Learning With Go. Implement Regression, Classification, Clustering, Time-series Models, Neural Networks, and More using the Go Programming Language
- ISBN: 9781785883903, 9781785883903
- Date of issue: 2017-09-26
- Format: Ebook
- Item ID: e_15pt
- Publisher: Packt Publishing