Skip to Content
Hands-On Automated Machine Learning
book

Hands-On Automated Machine Learning

by Sibanjan Das, Umit Mert Cakmak
April 2018
Beginner to intermediate content levelBeginner to intermediate
282 pages
6h 52m
English
Packt Publishing
Content preview from Hands-On Automated Machine Learning

Summary

In this chapter, you learned about many different aspects when it comes to choosing a suitable ML pipeline for a given problem.

Computational complexity, differences in training and scoring time, linearity versus non-linearity, and algorithm, specific feature transformations are valid considerations and it’s useful to look at your data from these perspectives.

You gained a better understanding of selecting suitable models and how machine learning pipelines work by practicing various use cases. You are starting to scratch the surface and this chapter was a good starting point to extend these skills.

In the next chapter, you will learn about optimizing hyperparameters and will be introduced to more advanced concepts, such as Bayesian-based ...

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

Automated Machine Learning

Automated Machine Learning

Adnan Masood
R: Unleash Machine Learning Techniques

R: Unleash Machine Learning Techniques

Raghav Bali, Dipanjan Sarkar, Brett Lantz, Cory Lesmeister

Publisher Resources

ISBN: 9781788629898Supplemental Content