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Fundamentals of Machine Learning$
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Thomas P. Trappenberg

Print publication date: 2019

Print ISBN-13: 9780198828044

Published to Oxford Scholarship Online: January 2020

DOI: 10.1093/oso/9780198828044.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 23 July 2021

Scientific programming with Python

Scientific programming with Python

Chapter:
(p.17) 2 Scientific programming with Python
Source:
Fundamentals of Machine Learning
Author(s):

Thomas P. Trappenberg

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198828044.003.0002

This chapter offers a brief introduction to scientific programming with Python with an emphasis on some mathematical operations that will form the basis of many algorithms. This will specifically include working with matrices and convolutions. Python is a high-level programming language similar to Matlab and R that has gained increasing popularity in the machine learning community. The main reason this book uses Python is that it is freely available and now provides considerable support for machine learning with packages such as sklearn and Keras that are discussed and utilized in this book. Some familiarity with programming concepts is assumed, and the chapter concentrates on a brief introduction to the specific environment and supporting libraries used throughout as well as some basic operations such as convolutions that will be important in later algorithms.

Keywords:   Python, Jupyter, basic programing, computer vision, convolution

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