Skip to Content
Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
book

Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

by Robert Johansson
September 2024
Intermediate to advanced content levelIntermediate to advanced
501 pages
17h 6m
English
Apress
Content preview from Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2024
R. JohanssonNumerical Pythonhttps://doi.org/10.1007/979-8-8688-0413-7_15

15. Machine Learning

Robert Johansson1  
(1)
Urayasu-shi, Chiba, Japan
 

This chapter explores machine learning. This topic is closely related to statistical modeling, which we considered in Chapter 14 because both use data to describe and predict outcomes of uncertain or unknown processes. The approach taken in statistical modeling emphasizes understanding how the data is generated by devising models that describe the underlying process behavior and fitting the model’s parameters to the observed data. If the model fits the data well and satisfies the relevant model assumptions, then the ...

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

Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

Robert Johansson
Machine Learning with Python

Machine Learning with Python

Tarkeshwar Barua, Kamal Kant Hiran, Ritesh Kumar Jain, Ruchi Doshi

Publisher Resources

ISBN: 9798868804137Purchase LinkPublisher Website