Achievements
- Provided consulting services in Computer Vision, MLOps, and Data Analytics for a multinational company, focusing on offline image recognition functionalities for mobile applications.
- Assisted in developing solutions for product detection and classification in supermarkets, handling large-scale data generated daily by international clients.
- Successfully implemented the solution on Google Cloud Platform (GCP), leveraging Google Kubernetes Engine (GKE) for scalability and reliability.
- Streamlined data organization and processing to enhance the accuracy and efficiency of image recognition.
Context
This project aimed to assist a multinational company in creating a mobile app with offline image recognition functionalities for detecting and classifying supermarket products. The solution needed to process vast amounts of data from the company’s international clients while ensuring efficient deployment and scalability.
Key components of the project included:
- Image Detection and Classification: Utilizing advanced computer vision techniques to identify and classify supermarket products.
- Data Organization: Processing and structuring large datasets generated by global operations to ensure seamless integration.
- Cloud Deployment: Implementing the solution on Google Cloud Platform (GCP) using Google Kubernetes Engine (GKE) to enable scalability and high availability.
Technologies Used
- Computer Vision Frameworks: For image recognition and classification.
- MLOps Practices: To streamline model deployment and maintenance.
- Google Cloud Platform (GCP): For robust and scalable cloud infrastructure.
- Google Kubernetes Engine (GKE): To manage and scale containerized applications.