Principles for Data Quality Measures

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Niraj Joshi

43:42

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01. Course Overview

01. Course Overview.mp4

01:14

02. Introducing Data Discovery and Cataloging

02. Introduction to the Course.mp4

01:32

03. Types of Machine Learning.mp4

03:52

04. Key Metrics to Assess Data Quality.mp4

01:55

05. Purpose of Data Cataloging.mp4

02:17

03. Evaluating Data Quality and Profiling

06. Benefits of Data Profiling.mp4

01:39

07. Domain Specific Data Quality Checks.mp4

01:09

08. Feature Engineering Pipeline.mp4

01:20

09. Demo- Data Profiling.mp4

08:01

10. Summary.mp4

00:23

04. Tracking Data Lineage and Governance

11. Introduction to Data Governance.mp4

01:39

12. Benefits of Data Lineage and Governance.mp4

03:11

13. Prerequisites to Train ML Model.mp4

00:52

14. Training the ML Model.mp4

01:45

15. Versioning ML as a Service.mp4

01:37

16. Summary.mp4

00:24

05. Exploring Best Practices for Metadata Management

17. Overview of MetaData Management.mp4

02:42

18. Effective Metadata Management Practices.mp4

02:11

19. MLMD Database.mp4

01:28

20. Demo-Assess Metadata of ML Model.mp4

04:09

21. Summary.mp4

00:22

Description

This course will teach you the aspects to understand MLOps journey, end to end data quality checks and establish the mechanism of data cataloging, principles around metadata management and data governance.

What You'll Learn?

Data quality is an important prerequisite prior to machine learning modelling. It is of utmost importance to thoroughly assess data quality before model building. In this course, Principles for Data Quality Measures, you’ll learn to build MLOps pipelinse and explore best practices for metadata management. First, you’ll explore data discovery and cataloging. Next, you’ll discover data profiling and quality checks. Finally, you’ll learn to explore data lineage and the best metadata management practices and analyze the MLOps cycle. By the end of this course, you’ll gain a better understanding of data discovery, profiling, and metadata management of the ML Model building process.

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Machine Learning

Data Science

Niraj Joshi

Instructor's Courses

Niraj is a AWS/Azure DevSecOps Cloud Specialist with over a decade of work experience into Data Modeling with Databases like Cassandra, MongoDB, SparkSQL, ElasticSearch and SQL Server. He has over 7 years of work ex into Computer Vision, Artificial Intelligence, DevOps, Machine Learning and Big Data Stack, he has been a consultant to companies like CISCO, ERICSSON, Dynamic Elements and JP Morgan He has excellent data visualization/ analytics skills and quite proficient in languages like Python , R, Julia and Octave.

Pluralsight

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Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.