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Principles of Data Science

You're reading from   Principles of Data Science Understand, analyze, and predict data using Machine Learning concepts and tools

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789804546
Length 424 pages
Edition 2nd Edition
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Tools
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Authors (3):
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Sunil Kakade Sunil Kakade
Author Profile Icon Sunil Kakade
Sunil Kakade
Sinan Ozdemir Sinan Ozdemir
Author Profile Icon Sinan Ozdemir
Sinan Ozdemir
Marco Tibaldeschi Marco Tibaldeschi
Author Profile Icon Marco Tibaldeschi
Marco Tibaldeschi
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Toc

Table of Contents (17) Chapters Close

Preface 1. How to Sound Like a Data Scientist FREE CHAPTER 2. Types of Data 3. The Five Steps of Data Science 4. Basic Mathematics 5. Impossible or Improbable - A Gentle Introduction to Probability 6. Advanced Probability 7. Basic Statistics 8. Advanced Statistics 9. Communicating Data 10. How to Tell If Your Toaster Is Learning – Machine Learning Essentials 11. Predictions Don't Grow on Trees - or Do They? 12. Beyond the Essentials 13. Case Studies 14. Building Machine Learning Models with Azure Databricks and Azure Machine Learning service Other Books You May Enjoy Index

Probability, odds, and log odds

We are familiar with the basic concept of probability in that the probability of an event occurring can be simply modeled as the number of ways the event can occur, divided by all of the possible outcomes. For example, if, out of 3,000 people who walked into a store, 1,000 actually bought something, then we could say that the probability of a single person buying an item is as follows:

Probability, odds, and log odds

However, we also have a related concept, called odds. The odds of an outcome occurring is the ratio of the number of ways that the outcome occurs divided by every other possible outcome instead of all possible outcomes. In the same example, the odds of a person buying something would be as follows:

Probability, odds, and log odds

This means that, for every customer you convert, you will not convert two customers. These concepts are so related that there is even a formula to get from one to the other. We have that here:

Probability, odds, and log odds

Let's check this out with our example, as illustrated here:

Probability, odds, and log odds

It checks out!

Let's use...

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