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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

Learning

I want you to think about how you learn. Not the learning styles, mind; no, I want you to give your learning process a long hard deep thought. Think of the various ways you learn. Maybe you've touched a stove while it's hot once. Or if you ever learned a new language, maybe you started out by memorizing phrases before becoming fluent. Think about all the chapters that had preceded this. What do they have in common?

In broad strokes, learning is done by means of corrections. If you touched a stove while it's hot, you made a mistake. The correction is to never touch a stove when it's hot ever again. You've learned how not to touch the stove while it's hot.

Similarly, the way a neural network learns is by means of correction. If we want to train a machine to learn to classify handwriting, we would need to provide some sample images, and tell...

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