MLOps at Acerta - Automating the Machine Learning Lifecycle for Manufacturing

Explore the implementation of MLOps at Acerta Analytics in this 34-minute conference talk from MLOps World: Machine Learning in Production. Discover how Acerta built a scalable ML platform from scratch to automate the machine learning lifecycle for manufacturing. Learn about the challenges of deploying and maintaining machine learning models in production, including handling increasing data volume, ensuring model robustness, and addressing data drift. Gain insights into the design and architecture of an ML platform that orchestrates the complete workflow of training, deploying, monitoring, and updating machine learning models across different environments. Understand the benefits of containerizing each step in the model lifecycle, from data ingestion to performance monitoring. Explore the key deliverables achieved through this MLOps implementation, including reusable infrastructure, end-to-end testing, robust versioning, model traceability, auto-retraining capabilities, reduced development cycles, real-time monitoring, and platform scalability. Learn from the experiences of Amit Jain, Director of Machine Learning, and Harika Gaggara, Data Scientist at Acerta Analytics, as they share their journey in building production-grade machine learning solutions for automotive manufacturers.