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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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Concepts
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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

A/B testing concepts

If you work as a data scientist at a web company, you'll probably be asked to spend some time analyzing the results of A/B tests. These are basically controlled experiments on a website to measure the impact of a given change. So, let's talk about what A/B tests are and how they work.

A/B tests

If you're going to be a data scientist at a big tech web company, this is something you're going to definitely be involved in, because people need to run experiments to try different things on a website and measure the results of it, and that's actually not as straightforward as most people think it is.

What is an A/B test? Well, it's a controlled experiment that you usually run on...

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