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Go Machine Learning Projects

You're reading from   Go Machine Learning Projects Eight projects demonstrating end-to-end machine learning and predictive analytics applications in Go

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788993401
Length 348 pages
Edition 1st Edition
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Author (1):
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Xuanyi Chew Xuanyi Chew
Author Profile Icon Xuanyi Chew
Xuanyi Chew
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Table of Contents (12) Chapters Close

Preface 1. How to Solve All Machine Learning Problems 2. Linear Regression - House Price Prediction FREE CHAPTER 3. Classification - Spam Email Detection 4. Decomposing CO2 Trends Using Time Series Analysis 5. Clean Up Your Personal Twitter Timeline by Clustering Tweets 6. Neural Networks - MNIST Handwriting Recognition 7. Convolutional Neural Networks - MNIST Handwriting Recognition 8. Basic Facial Detection 9. Hot Dog or Not Hot Dog - Using External Services 10. What's Next? 11. Other Books You May Enjoy

What is MachineBox?

MachineBox is a service, first and foremost. The machine learning algorithms are packaged nicely as a cloud service. Further, because MachineBox cares about the developer experience, they have provided SDKs and local instances for you to develop against. This comes in the form of containers. Set up Docker, run the commands found on the MachineBox website, and you're done!

In this project, we wish to use a facial-recognition system to recognize faces. MachineBox provides such a service, called facebox.

Signing in and up

First, we need to sign into MachineBox. Go to https://machinebox.io and click on Sign Up. Conveniently, the sign in page is the same. MachineBox will then email you a link. Clicking...

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