Book

Machine Learning With Go

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 Data scientists and analysts are unfortunately known for producing bad, inefficient, and unmaintainable code. This book will address this issue, and will clearly show readers how to be productive with machine learning while also producing application maintaining a high level of integrity. It will also allow readers to overcome the common challenges of integrating analysis and machine learning code within an existing engineering organization.

Offered byPackt Logo

Difficulty Level
Intermediate
Completion Time
10h8m approx.
Language
English
Certification
Not available

About Course

Book Content

chapters 10h8m total length

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

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