Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
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
Reproducible Data Science with Pachyderm

You're reading from   Reproducible Data Science with Pachyderm Learn how to build version-controlled, end-to-end data pipelines using Pachyderm 2.0

Arrow left icon
Product type Paperback
Published in Mar 2022
Publisher Packt
ISBN-13 9781801074483
Length 364 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Svetlana Karslioglu Svetlana Karslioglu
Author Profile Icon Svetlana Karslioglu
Svetlana Karslioglu
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Introduction to Pachyderm and Reproducible Data Science
2. Chapter 1: The Problem of Data Reproducibility FREE CHAPTER 3. Chapter 2: Pachyderm Basics 4. Chapter 3: Pachyderm Pipeline Specification 5. Section 2:Getting Started with Pachyderm
6. Chapter 4: Installing Pachyderm Locally 7. Chapter 5: Installing Pachyderm on a Cloud Platform 8. Chapter 6: Creating Your First Pipeline 9. Chapter 7: Pachyderm Operations 10. Chapter 8: Creating an End-to-End Machine Learning Workflow 11. Chapter 9: Distributed Hyperparameter Tuning with Pachyderm 12. Section 3:Pachyderm Clients and Tools
13. Chapter 10: Pachyderm Language Clients 14. Chapter 11: Using Pachyderm Notebooks 15. Other Books You May Enjoy

Reviewing the standard Pachyderm workflow

As you probably noticed when you were creating a pipeline, there is a certain workflow that you will need to follow when working with Pachyderm. Depending on your automation tools, your team processes, and the software that you use, it might differ, but in general, it boils down to the following common steps:

  1. Add your data to Pachyderm.
  2. Create a pipeline or pipelines.
  3. Add more data.
  4. Modify the parameters.
  5. Modify your pipeline or pipelines.
  6. Output the result to an output repository.
  7. Repeat Steps 3–6 as many times as needed or continuously.
  8. Serve your model or package your library and make it available for use.

The following diagram demonstrates this process:

Figure 7.1 – Pachyderm workflow

Depending on whether you keep your code in a Docker image, in the pipeline itself, or you use a build pipeline with your Python code, you need to rebuild your Docker image every...

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 $19.99/month. Cancel anytime