Data Duplication Removal Using Machine learning

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

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

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