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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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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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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

Linear algebra

Remember the movie recommendation engine we looked at earlier? What if we had 10,000 movies to recommend and we had to choose only 10 to give to the user? We'd have to take a dot product between the user profile and each of the 10,000 movies. Linear algebra provides the tools to make these calculations much more efficient.

It is an area of mathematics that deals with the math of matrices and vectors. It has the aim of breaking down these objects and reconstructing them in order to provide practical applications. Let's look at a few linear algebra rules before proceeding.

Matrix multiplication

Like numbers, we can multiply matrices together. Multiplying matrices is, in essence, a mass-produced way of taking several dot products at once. Let's, for example, try to multiply the following matrices:

Matrix multiplication

We need to consider a couple of things:

  • Unlike numbers, multiplication of matrices is not commutative, meaning that the order in which you multiply matrices matters a great...
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