https://github.com/projects-developer/data-duplication-removal-using-machine-learning

This project utilizes machine learning algorithms to detect and remove duplicate data entries from a dataset. Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials
https://github.com/projects-developer/data-duplication-removal-using-machine-learning

btechprojects computerscienceprojects dataanalytics datacleaning dataduplicationremoval datamanagement datamatching dataquality duplicatedetection machinelearning mtechprojects

Last synced: 7 months ago
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This project utilizes machine learning algorithms to detect and remove duplicate data entries from a dataset. Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials

• Host: GitHub
• URL: https://github.com/projects-developer/data-duplication-removal-using-machine-learning
• Owner: Projects-Developer
• Created: 2024-12-24T09:02:01.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2025-01-18T12:18:55.000Z (9 months ago)
• Last Synced: 2025-01-18T13:33:21.798Z (9 months ago)
• Topics: btechprojects, computerscienceprojects, dataanalytics, datacleaning, dataduplicationremoval, datamanagement, datamatching, dataquality, duplicatedetection, machinelearning, mtechprojects
• Homepage: https://www.finalproject.in/
• Size: 5.86 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

          
# Data Duplication Removal Using Machine learning

Data Duplication Removal Using Machine learning Code, Document And Video Tutorial

![Data Duplication](https://github.com/user-attachments/assets/82614e7e-4391-45e9-a7e2-c3e1aecf7eaa)

## Youtube link: https://youtu.be/_b_7sjDpuC0?si=A7bo6aVFQ3YFKVXY

## Abstract:

Data duplication is a pervasive issue in data management, leading to inaccuracies, inconsistencies, and inefficiencies. This study proposes a machine learning-based approach for detecting and removing duplicate data entries. By leveraging natural language processing and data matching techniques, our system achieves high accuracy and efficiency in identifying and eliminating redundant information. Experimental results demonstrate the effectiveness of our approach in improving data quality and reducing storage costs. This research has significant implications for data-driven applications, business intelligence, and decision-making.

Keywords: Data Duplication Removal, Machine Learning, Natural Language Processing, Data Matching, Data Quality, Data Cleaning, Data Preprocessing, Duplicate Detection, Data Management.

### Project include: 

1. Synopsis

2. PPT

3. Research Paper

4. Code

5. Explanation video

6. Documents

7. Report

### Need Code, Documents & Explanation video ? 

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