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Data Analysis with Python and Python Project Portfolio

Welcome to my portfolio of Python projects and data analysis techniques! In this README, I'll provide an overview of my skills and highlight some of my key projects.

Skills and Expertise

I have developed proficiency in various data analysis and visualization tools and techniques, including:

  • Python, Pandas, NumPy, Seaborn, and Matplotlib for data manipulation and visualization.
  • Python for Hospitality Analysis, where I applied data processing and visualization skills to optimize operations and enhance guest experiences.
  • Building a Backend Project for Medical Data Extraction, a robust project that involved various technologies and skills.

Projects

Python for Hospitality Analysis 🏨

In this project, I leveraged Python to analyze hospitality data, deriving valuable insights to optimize operations and enhance guest experiences. This project strengthened my understanding of real-world data analysis scenarios.

Building a Backend Project for Medical Data Extraction 💻

The highlight of my portfolio is this robust backend project for medical data extraction. Here's an overview of the steps involved:

  1. Document Conversion: Using PyPDF, I converted scanned old documents into images for further processing.
  2. Image Enhancement: Employing OpenCV, I used thresholding concepts to ensure image stability and enhance clarity.
  3. Text Extraction: Utilizing the pytesseract OCR engine, I extracted meaningful information from the images.
  4. Data Extraction: Employing regular expressions (regex), I extracted the required data fields for frontend compatibility.
  5. Server-Side Application: Leveraging FastAPI, I built a server-side application to handle requests and retrieve the necessary data. This all-in-one solution can be viewed as an OCR-based in-house engine, specifically designed for mid and small-cap companies, medical centers, and hospitals.
  6. Unit Testing: To ensure the project's quality and reliability, I incorporated robust unit testing using the pytest module. This ensured that the application functions as intended, providing accurate and dependable results.

The benefits of this project are substantial:

  • Streamlines data extraction from scanned documents, ensuring accuracy and efficiency.
  • Minimizes the need for manual data entry, saving valuable time and resources.
  • Enhances the utilization of manpower, allowing staff to focus on higher-value tasks.
  • Enables medical centers and hospitals to access prescription details and patient information instantly, facilitating better patient care.

Acknowledgments

I want to express my gratitude to the codebasics and Dhaval Patel team for offering such a comprehensive and enriching course. These skills and projects have equipped me to make a positive impact in the real world.

Feel free to explore my individual project repositories for more in-depth information.

  • [Hospitality Analysis Project]
  • [Medical Data Extraction Project]

Thank you for visiting my portfolio, and I look forward to further expanding my knowledge and working on exciting projects!

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