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This desktop application automates the creation of customs import templates for SAT compliance. Built entirely in Python, the tool reads commercial invoices and quality certificates in PDF format. It extracts critical data such as shipping dates, pricing, weights, and chemical compositions using regular expressions and data frames. The system then processes this information to dynamically generate a fully formatted Microsoft Word document. Packaged as a standalone executable with a clean graphical user interface, it replaces a manual, error-prone data entry process with a fast, reliable, and standardized automated solution.
Turning PDF invoices into ready to file SAT templates in one click slashes the manual entry time.
exactly and not only entry time, but also in hole process, because there is not only one invoice to process, sometimes are more than 3 and there is where you save time, your time!
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Proud to officially add the AWS Certified Machine Learning Engineer - Associate certification to my toolkit!
Building robust machine learning pipelines and scaling AI workloads securely on the cloud has always been a key focus of mine. Earning this certification has been a great deep-dive into mastering AWS ML infrastructure, MLOps best practices, and production-grade architectures.
Ready to bring these advanced capabilities to upcoming data science and engineering projects! Let's build something impactful. 💡💪
🔗 Verify Certificate:
Validation Number: 74c5808986a64b84addcaa9db725b8bd
Verification Link: https://aws.amazon.com/verification
#AWS #MachineLearning #AI #CloudComputing #DataAnalysis #MLOps
Congratulations on earning the AWS Machine Learning Engineer certification, Hazem khaled! Robust pipelines and cloud automation make all the difference for production-grade AI systems.
Data entry copy paste pdf word website research and data collection
Headless Document Automation & PDF Compilation Pipeline
Engineered a localized Python script to automate the layout generation and compilation of high-end professional data documents.
Key Technical Highlights:
• Developed a custom document formatting tool utilizing the python-docx framework.
• Integrated headless LibreOffice compiler commands (libreoffice --headless --convert-to pdf) to compile raw assets instantly via local terminal pipelines.
• Applied strict design constraints (A4 frameworks with tight 0.75-inch defensive margins) optimized to pass strict corporate Applicant Tracking Systems (ATS) parsing layers.
