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Hands-On Data Science and Python Machine Learning

You're reading from   Hands-On Data Science and Python Machine Learning Perform data mining and machine learning efficiently using Python and Spark

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787280748
Length 420 pages
Edition 1st Edition
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Author (1):
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Frank Kane Frank Kane
Author Profile Icon Frank Kane
Frank Kane
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Table of Contents (11) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Statistics and Probability Refresher, and Python Practice 3. Matplotlib and Advanced Probability Concepts 4. Predictive Models 5. Machine Learning with Python 6. Recommender Systems 7. More Data Mining and Machine Learning Techniques 8. Dealing with Real-World Data 9. Apache Spark - Machine Learning on Big Data 10. Testing and Experimental Design

Machine learning and train/test

So what is machine learning? Well, if you look it up on Wikipedia or whatever, it'll say that it is algorithms that can learn from observational data and can make predictions based on it. It sounds really fancy, right? Like artificial intelligence stuff, like you have a throbbing brain inside of your computer. But in reality, these techniques are usually very simple.

We've already looked at regressions, where we took a set of observational data, we fitted a line to it, and we used that line to make predictions. So by our new definition, that was machine learning! And your brain works that way too.

Another fundamental concept in machine learning is something called train/test, which lets us very cleverly evaluate how good a machine learning model we've made. As we look now at unsupervised and supervised learning, you'll see why...

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