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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

Data science in Data Cloud

Data science transcends traditional boundaries in the Data Cloud ecosystem, offering a dynamic environment where data scientists can harness the power of distributed computing and advanced analytics. With the ability to seamlessly integrate various data sources, including structured and unstructured data, Data Cloud provides a data exploration and experimentation environment. We will start this section with a brief data science and ML refresher.

Data science and ML concepts

Data science and ML have surged to the forefront of technological and business innovation, becoming integral components of decision-making, strategic planning, and product development across virtually all industries. The journey to their current popularity and influence is a testament to several factors, including advancements in technology, the explosion of data, and the increasing computational power available. This section will briefly discuss data science and ML concepts.

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