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An Introduction to Entity Resolution in Python

Gain insights into entity resolution in Python, covering business use cases, semantic preprocessing, graph clustering, and weak supervision. Increase business value through hands-on coding and strategic decision-making.

Advanced

63 Lessons

8h

Certificate of Completion

Gain insights into entity resolution in Python, covering business use cases, semantic preprocessing, graph clustering, and weak supervision. Increase business value through hands-on coding and strategic decision-making.
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Explanations

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Explanations

This course includes

1 Project
1 Assessment
192 Playgrounds
7 Quizzes
Course Overview
What You'll Learn
Course Content
Recommendations

Course Overview

A typical business stores data across multiple systems, including ERPs for operations, a CRM for marketing, files, notebooks, and BI apps for other purposes. Records of the same customer (entity) exist in multiple places, likely not in sync across nor unique within sources. This inconsistent situation generates an opportunity for us to drive business value by cross-referencing and deduplicating records with entity resolution. This course covers business acumen and hands-on coding. It starts with several bu...Show More
A typical business stores data across multiple systems, including ERPs for operations, a CRM for marketing, files, notebooks, an...Show More

What You'll Learn

The ability to deduplicate records using Python
Familiarity with an entity resolution framework and business cases
An understanding of semantic similarity and search
Experience with classification in the context of entity resolution
Hands-on experience in data-centric AI using weak supervision and confident learning
The ability to deduplicate records using Python

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Course Content

1.

Introduction to Entity Resolution and Applications

7 Lessons

Learn how to use entity resolution techniques in Python to improve data quality and integration.

2.

A Quickstart Guide Using the RecordLinkage Package

8 Lessons

Get started with entity resolution in Python using text preprocessing, similarity scoring, and evaluation techniques.

4.

Indexing

6 Lessons

Apply your skills to enhance the efficiency of entity resolution using various indexing techniques.

5.

Feature Engineering

5 Lessons

Deepen your knowledge of feature engineering for entity resolution, exploring various similarity methods.

7.

Clustering

6 Lessons

Piece together the parts of clustering techniques to improve classification accuracy in entity resolution.

11.

Conclusion

1 Lessons

Look at essential insights and skills for effective entity resolution in various systems.

12.

Appendix

3 Lessons

Examine batch geocoding, vector search with LanceDB, and essential resources for entity resolution.

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