Skip to Content
Learn Python by Building Data Science Applications
book

Learn Python by Building Data Science Applications

by Philipp Kats, David Katz
August 2019
Beginner
482 pages
12h 56m
English
Packt Publishing
Content preview from Learn Python by Building Data Science Applications

Concurrency and parallelism

Concurrency is the simultaneous execution of multiple pieces of code. Theoretically, concurrency can significantly increase the speed of code execution and it is widely used in software. For example, tasks that require some sort of big loop that does exactly the same operation many times with no interaction between those operations (for example, vectorized operations on dataset columns) are often called embarrassingly parallel and present a good target for concurrent execution. That being said, it has its limitations and suits some tasks (for example, where a number of tasks are independent of each other) better than others—read about Amdahl's law for some theoretical background. 

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Python for Data Science

Python for Data Science

Yuli Vasiliev
Introduction to Machine Learning with Python

Introduction to Machine Learning with Python

Andreas C. Müller, Sarah Guido

Publisher Resources

ISBN: 9781789535365Supplemental Content