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The Ultimate Guide to Snowpark

You're reading from   The Ultimate Guide to Snowpark Design and deploy Snowflake Snowpark with Python for efficient data workloads

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781805123415
Length 254 pages
Edition 1st Edition
Languages
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Authors (2):
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Shankar Narayanan SGS Shankar Narayanan SGS
Author Profile Icon Shankar Narayanan SGS
Shankar Narayanan SGS
Vivekanandan SS Vivekanandan SS
Author Profile Icon Vivekanandan SS
Vivekanandan SS
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Toc

Table of Contents (14) Chapters Close

Preface 1. Part 1: Snowpark Foundation and Setup
2. Chapter 1: Discovering Snowpark FREE CHAPTER 3. Chapter 2: Establishing a Foundation with Snowpark 4. Part 2: Snowpark Data Workloads
5. Chapter 3: Simplifying Data Processing Using Snowpark 6. Chapter 4: Building Data Engineering Pipelines with Snowpark 7. Chapter 5: Developing Data Science Projects with Snowpark 8. Chapter 6: Deploying and Managing ML Models with Snowpark 9. Part 3: Snowpark Applications
10. Chapter 7: Developing a Native Application with Snowpark 11. Chapter 8: Introduction to Snowpark Container Services 12. Index 13. Other Books You May Enjoy

Summary

Snowpark ML emerges as a versatile and powerful tool for data scientists, enabling them to tackle complex data science tasks within Snowflake’s unified data platform. Its integration with popular programming languages, scalability, and real-time processing capabilities make it invaluable for various applications, from predictive modeling to real-time analytics and advanced AI tasks. With Snowpark ML, organizations can harness the full potential of their data, drive innovation, and gain a competitive edge in today’s data-driven landscape.

In the next chapter, we will continue by deploying the model in Snowflake and operationalizing it.

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