Leo's Projects

Project 1: AI Music Video Generator

Led the development of an AI-powered music video generator, leveraging advanced AI technologies to produce personalized music videos.

  • Architecture Design: Utilized AWS services including Lambda for serverless computing, S3 for storage, API Gateway for API management, and CloudFormation for infrastructure as code (IaC).
  • Infrastructure as Code: Managed all AWS resources using CloudFormation, ensuring repeatable and version-controlled deployments.
  • Data Pipeline: Employed AWS CLI and SQS for queue management and reliable message delivery between services.
  • Backend Development: Created a Python backend to handle video processing and music generation using AI models.
  • DynamoDB Integration: Utilized DynamoDB for storing metadata and processing statuses, ensuring fast and scalable data access.
  • Monitoring and Debugging: Implemented CloudWatch Logs for monitoring and debugging, improving system reliability and performance.
  • CORS Configuration: Configured CORS in API Gateway to ensure secure and proper interaction between the frontend and backend.
  • Pre-signed URLs: Implemented pre-signed URLs for secure and temporary access to S3 objects, facilitating secure data transfer.
  • Front-End Interface: Developed an interactive user interface with HTML, CSS, and JavaScript for seamless user experience.
  • Scalability and Reliability: Ensured the system's ability to handle multiple concurrent video processing requests, maintaining high availability and fault tolerance.

Project 2: Cloud Resume Challenge

Completed the Cloud Resume Challenge by building a serverless web application, demonstrating proficiency in cloud technologies and infrastructure as code.

  • Static Website Hosting: Deployed a static website on AWS S3 with a custom domain name for a professional online presence.
  • Visitor Counter Implementation: Integrated DynamoDB, API Gateway, and Lambda to create a scalable and serverless visitor counter.
  • Continuous Deployment: Automated deployment processes using GitHub Actions, ensuring efficient and consistent updates.
  • Security Best Practices: Implemented AWS IAM policies to follow the principle of least privilege, enhancing the security of cloud resources.
  • CloudFormation: Used CloudFormation templates to manage and provision AWS infrastructure, ensuring consistent and repeatable deployments.

Project 3: Automated Audio Transcription and Editing Tool

Developed a Python tool to automate the transcription and editing of audio files, streamlining content creation workflows.

  • Transcription Automation: Utilized speech-to-text APIs to transcribe audio files, providing accurate and efficient transcription.
  • Keyword Timestamping: Implemented functionality to generate timestamps for keywords, enabling easy navigation within transcripts.
  • Audio Editing with FFmpeg: Used FFmpeg to automatically cut and edit audio files based on generated timestamps, enhancing the editing process.
  • User Interface: Developed a graphical user interface (GUI) for easy and intuitive use, facilitating integration into various workflows.
  • Integration and Scalability: Ensured the tool's ability to handle large audio files and multiple transcription tasks simultaneously.