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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 FREE CHAPTER 2. Linear Regression - House Price Prediction 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

Summary

In closing, it's only fair to mention that MachineBox does have some limitations for its free tiers; but for personal projects, in my experience, you won't run into them. Despite my personal reservations on the various machine learning-as-a-service systems out there, I do think they provide value. I have used them from time to time, but I generally do not need them. Nevertheless, I highly recommend that the reader check them out.

This chapter, in combination with the previous chapter, has shown the breadth of machine learning in the industry. Not all machine learning algorithms have to be handwritten from scratch if your main problem does not call for it. I am lucky enough to have a career in doing what I love: building customized machine learning algorithms. This may have tainted my views on this issue. You may be an engineer on a deadline who has to solve some...

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