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 by
Difficulty Level
Intermediate
Completion Time
10h8m
Language
English
About Book
Who Is This Book For?
This book is for Go developers who are familiar with the Go syntax and can develop, build, and run basic Go programs. If you want to explore the field of machine learning and you love Go, then this book is for you! Machine Learning with Go will give readers the practical skills to perform the most common machine learning tasks with Go. Familiarity with some statistics and math topics is necessary.
Machine Learning With Go
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 10h8m total length
Gathering and Organizing Data
Matrices, Probability, and Statistics
Evaluation and Validation
Regression
Classification
Clustering
Time Series and Anomaly Detection
Neural Networks and “Deep” Learning
Deploying and distributing Analyses and Models
Appendix: Algorithms/Techniques Related to ML
Related Resources
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