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

Technical requirements

For this chapter, you will need to have the Anaconda distribution installed. This will come with conda, Navigator, and the most widely used tools for data science, including all the packages we will use later in the chapter.

You'll need to have a GitHub account set up before you begin. Head to https://github.com/join to do that.

You can find the code for this chapter and the rest of the book here: https://github.com/PacktPublishing/Building-Data-Science-Solutions-with-Anaconda/tree/main/Chapter02.

We'll also be writing and editing code. An integrated developer environment (IDE) of choice such as Visual Studio Code can be used but its suggested you use the very popular Jupyter Notebook for the tasks that we will be doing in this chapter. Jupyter is included in the Anaconda distribution.

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 €18.99/month. Cancel anytime