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Data Processing with Optimus

You're reading from   Data Processing with Optimus Supercharge big data preparation tasks for analytics and machine learning with Optimus using Dask and PySpark

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781801079563
Length 300 pages
Edition 1st Edition
Languages
Concepts
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Authors (2):
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Dr. Argenis Leon Dr. Argenis Leon
Author Profile Icon Dr. Argenis Leon
Dr. Argenis Leon
Luis Aguirre Contreras Luis Aguirre Contreras
Author Profile Icon Luis Aguirre Contreras
Luis Aguirre Contreras
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Getting Started with Optimus
2. Chapter 1: Hi Optimus! FREE CHAPTER 3. Chapter 2: Data Loading, Saving, and File Formats 4. Section 2: Optimus – Transform and Rollout
5. Chapter 3: Data Wrangling 6. Chapter 4: Combining, Reshaping, and Aggregating Data 7. Chapter 5: Data Visualization and Profiling 8. Chapter 6: String Clustering 9. Chapter 7: Feature Engineering 10. Section 3: Advanced Features of Optimus
11. Chapter 8: Machine Learning 12. Chapter 9: Natural Language Processing 13. Chapter 10: Hacking Optimus 14. Chapter 11: Optimus as a Web Service 15. Other Books You May Enjoy

Summary

In this chapter, we did a deep dive into how Optimus was built and helped you learn how to expand what Optimus can do, from creating a new engine to loading and saving data and processing string and numeric data.

This can give you a lot of flexibility. You also learned how to build a full-fledged frontend interface in which you can use Optimus as the backend to process data on any of the engines that are available.

In the next chapter, we will talk about the Optimus server and how you can use it to process data using an easy-to-use API.

If you find any other inconsistencies in the API, please let us know.

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