Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Building Data Science Solutions with Anaconda

You're reading from   Building Data Science Solutions with Anaconda A comprehensive starter guide to building robust and complete models

Arrow left icon
Product type Paperback
Published in May 2022
Publisher Packt
ISBN-13 9781800568785
Length 330 pages
Edition 1st Edition
Arrow right icon
Author (1):
Arrow left icon
Dan Meador Dan Meador
Author Profile Icon Dan Meador
Dan Meador
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1: The Data Science Landscape – Open Source to the Rescue
2. Chapter 1: Understanding the AI/ML landscape FREE CHAPTER 3. Chapter 2: Analyzing Open Source Software 4. Chapter 3: Using the Anaconda Distribution to Manage Packages 5. Chapter 4: Working with Jupyter Notebooks and NumPy 6. Part 2: Data Is the New Oil, Models Are the New Refineries
7. Chapter 5: Cleaning and Visualizing Data 8. Chapter 6: Overcoming Bias in AI/ML 9. Chapter 7: Choosing the Best AI Algorithm 10. Chapter 8: Dealing with Common Data Problems 11. Part 3: Practical Examples and Applications
12. Chapter 9: Building a Regression Model with scikit-learn 13. Chapter 10: Explainable AI - Using LIME and SHAP 14. Chapter 11: Tuning Hyperparameters and Versioning Your Model 15. Other Books You May Enjoy

Summary

In this chapter, we covered a lot of ground. We looked at what it means to be open source by digging into how the OSI defines it as a common understanding that the source code should be accessible, open to change, and not limited by industry, among other things.

We found out about the major licenses that you'll come across on your journey and the differences between them. You saw that copyleft licenses such as GPL require you to share anything you create, but permissive licenses give you permission to keep those things for yourself, like MIT licenses do.

We then looked at the criteria that you can use to evaluate whether an open source tool might be for you by using things such as the number of GitHub stars, the number of maintainers, and how long it's been around. Looking at some of these things holistically lets us put together a better picture of whether we can count on our OSS tool to be maintained and reliable.

Finally, we saw how you can access the...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at R$50/month. Cancel anytime