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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

Real data

Up to this point, we've been working on an example JSON that the Twitter documentation provides. I assume by now you have your Twitter API access. So, let's get real Twitter data!

To get your API keys from the developer portal, click on the Get Started link. You will come to a page such as this:

Select Create an app. You will be brought to a page that looks like this:

I had previously created a Twitter app a long time ago (it had very similar features to the one we're creating in this project); hence, I have an app there already. Click on the blue Create an app button at the top right. You will be brought to the following form:

Fill in the form then click submit. It might take a few days before you receive an email saying the app has been approved for development. Be sure to be truthful in the description. Lastly, you should then be able to click into...

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