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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

Classification - Spam Email Detection

What makes you you? I have dark hair, pale skin, and Asiatic features. I wear glasses. My facial structure is vaguely round, with extra subcutaneous fat in my cheeks compared to my peers. What I have done is describe the features of my face. Each of these features described can be thought of as a point within a probability continuum. What is the probability of having dark hair? Among my friends, dark hair is a very common feature, and so are glasses (a remarkable statistic is out of the 300 people or so I polled on my Facebook page, 281 of them require prescription glasses). The epicanthic folds of my eyes are probably less common, as is the extra subcutaneous fat in my cheeks.

Why am I bringing up my facial features in a chapter about spam classification? It's because the principles are the same. If I show you a photo of a human face...

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