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NumPy Essentials

You're reading from  NumPy Essentials

Product type Book
Published in Apr 2016
Publisher
ISBN-13 9781784393670
Pages 156 pages
Edition 1st Edition
Languages
Concepts
Authors (3):
Leo (Liang-Huan) Chin Leo (Liang-Huan) Chin
Profile icon Leo (Liang-Huan) Chin
LinkedIn
Leo (Liang-Huan) Chin is a data engineer with more than 5 years of experience in the field of Python. He works for Gogoro smart scooter, Taiwan, where his job entails discovering new and interesting biking patterns . His previous work experience includes ESRI, California, USA, which focused on spatial-temporal data mining. He loves data, analytics, and the stories behind data and analytics. He received an MA degree of GIS in geography from State University of New York, Buffalo. When Leo isn't glued to a computer screen, he spends time on photography, traveling, and exploring some awesome restaurants across the world. You can reach Leo at http://chinleock.github.io/portfolio/.
See other products by Leo (Liang-Huan) Chin
Tanmay Dutta Tanmay Dutta
Profile icon Tanmay Dutta
LinkedIn
Tanmay Dutta is a seasoned programmer with expertise in programming languages such as Python, Erlang, C++, Haskell, and F#. He has extensive experience in developing numerical libraries and frameworks for investment banking businesses. He was also instrumental in the design and development of a risk framework in Python (pandas, NumPy, and Django) for a wealth fund in Singapore. Tanmay has a master's degree in financial engineering from Nanyang Technological University, Singapore, and a certification in computational finance from Tepper Business School, Carnegie Mellon University.
See other products by Tanmay Dutta
Shane Holloway Shane Holloway
Profile icon Shane Holloway
LinkedIn
http://shaneholloway.com/resume/
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Table of Contents (16) Chapters

NumPy Essentials
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. An Introduction to NumPy 2. The NumPy ndarray Object 3. Using NumPy Arrays 4. NumPy Core and Libs Submodules 5. Linear Algebra in NumPy 6. Fourier Analysis in NumPy 7. Building and Distributing NumPy Code 8. Speeding Up NumPy with Cython 9. Introduction to the NumPy C-API 10. Further Reading

Chapter 5. Linear Algebra in NumPy

NumPy is designed for numeric computations; underneath the hood it is still the powerful ndarray object, but at the same time NumPy provides different types of objects to solve mathematical problems. In this chapter, we will cover the matrix object and polynomial object to help you solve problems using a non-ndarray way. Again, NumPy provides a lot of standard mathematical algorithms and supports multi-dimensional data. While a matrix can't perform three-dimensional data, using the ndarray objects with the NumPy functions of linear algebra and polynomials is more preferable (the extensive SciPy library is another good choice for linear algebra, but NumPy is our focus in this book). Let's use NumPy to do some math now!

The topics that will be covered in this chapter are:

  • Matrix and vector operations
  • Decompositions
  • Mathematics of polynomials
  • Regression and curve fitting
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Authors (3)

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Profile icon Leo (Liang-Huan) Chin
LinkedIn
Leo (Liang-Huan) Chin is a data engineer with more than 5 years of experience in the field of Python. He works for Gogoro smart scooter, Taiwan, where his job entails discovering new and interesting biking patterns . His previous work experience includes ESRI, California, USA, which focused on spatial-temporal data mining. He loves data, analytics, and the stories behind data and analytics. He received an MA degree of GIS in geography from State University of New York, Buffalo. When Leo isn't glued to a computer screen, he spends time on photography, traveling, and exploring some awesome restaurants across the world. You can reach Leo at http://chinleock.github.io/portfolio/.
Read more
See other products by Leo (Liang-Huan) Chin
Profile icon Tanmay Dutta
LinkedIn
Tanmay Dutta is a seasoned programmer with expertise in programming languages such as Python, Erlang, C++, Haskell, and F#. He has extensive experience in developing numerical libraries and frameworks for investment banking businesses. He was also instrumental in the design and development of a risk framework in Python (pandas, NumPy, and Django) for a wealth fund in Singapore. Tanmay has a master's degree in financial engineering from Nanyang Technological University, Singapore, and a certification in computational finance from Tepper Business School, Carnegie Mellon University.
Read more
See other products by Tanmay Dutta
Profile icon Shane Holloway
LinkedIn
http://shaneholloway.com/resume/
See other products by Shane Holloway
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