In this session, we will tackle the challenge of automated quality inspection in manufacturing. Using image data, you’ll learn to build, train, and deploy a defect detection model that enhances product quality and operational efficiency. By the end, you'll understand the complete pipeline from data collection to cloud deployment and monitoring.
Session Flow: Data Collection => EDA => Processing => Model Building => Model Deployment on Azure => Monitoring on Azure
Agenda for the session
- Gather and preprocess image data for defect analysis
- Build and train a CNN model using transfer learning
- Deploy the trained model on Azure for scalability
- Monitor model performance using cloud-based tools
About Speakers
Anjana Agrawal
Entrepreneur | IoT, Big Data, Business Analytics & IT/Operations Consultant
A seasoned professional with 30+ years of expertise in data science, strategy, and business transformation. Skilled in advanced statistical modeling, machine learning, NLP, and big data analytics. Recognised kaggle competition expert with top global rankings. Combines deep expertise as a management consultant, technical architect, and quality leader (ISO, CMMi, Six Sigma) with a strong track record in digital transformation, cloud, SOA, and social media analytics.
