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Personalized Media Platform for Enhanced User Engagement

Personalized Media Platform for Enhanced User Engagement

Personalized Media Platform  for Enhanced User Engagement

We built a powerful media personalization platform that delivers real-time curated news and video to millions. Using machine learning and advanced cloud infrastructure, the system adapts to user preferences and behavior for maximum relevance and engagement.

Industry

AdTech

Client

Mobihunter

Region

Hong Kong

Year

2025

Technologies:

AWS
gitlab
Python
Docker
Apache Superset
TensorFlow
AirFlow
Google Cloud

Business Impacts

  • Personalized recommendations, boosting user retention and engagement
  • Scalable architecture supported millions of real-time interactions with minimal latency
  • Streamlined operations reduced manual workloads and improved cost efficiency
  • Advanced analytics provided critical insights for marketing and strategic planning

Technical Highlights

  • Machine learning: implemented TensorFlow-based models for precise content recommendations
  • Real-time data processing: built pipelines with Airflow for ingesting and processing millions of user interactions daily
  • Automation: CI/CD pipelines using Docker and GitLab CI for seamless updates and feature rollouts
  • Automation: CI/CD pipelines using Docker and GitLab CI for seamless updates and feature rollouts
  • Performance monitoring: utilized AWS tools for infrastructure reliability and high availability
  • Data visualization: integrated Apache Superset for actionable reporting and business insights
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