https://github.com/compcode1/analysis-synthetic-dataset-optimization-techniques
This project focuses on the critical analysis of synthetic health metrics and the optimization of advanced algorithms used for data processing and analysis.
https://github.com/compcode1/analysis-synthetic-dataset-optimization-techniques
comparisons dataset efficiency utility
Last synced: 10 months ago
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This project focuses on the critical analysis of synthetic health metrics and the optimization of advanced algorithms used for data processing and analysis.
- Host: GitHub
- URL: https://github.com/compcode1/analysis-synthetic-dataset-optimization-techniques
- Owner: Compcode1
- Created: 2024-06-30T22:05:14.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-07-04T01:12:04.000Z (over 1 year ago)
- Last Synced: 2025-03-18T01:15:54.834Z (10 months ago)
- Topics: comparisons, dataset, efficiency, utility
- Language: Jupyter Notebook
- Homepage:
- Size: 17.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Critical Analysis of Synthetic Health Metrics and Advanced Algorithm Optimization
## Introduction
This project focuses on the critical analysis of synthetic health metrics and the optimization of advanced algorithms used for data processing and analysis.
## Objectives
1. Assess the accuracy/ viability of synthetic health data.
2. Optimize data processing algorithms for efficiency.
## Files
- `Critical Analysis of Synthetic Health Metrics and Advanced Algorithm Optimization1.ipynb`: The main Jupyter Notebook containing the analysis.
- `data/`: Directory containing the dataset files.
- `src/`: Source code for data analysis and processing.
## Installation
To run this project, you need to have Python and Jupyter Notebook installed. You can install the required packages using:
```bash
pip install -r requirements.txt