- March 10, 2022
- 11.00AM To 12.00PM
MLOps - A key lever in revolutionizing AI/ML adoption for industries
March 10, 2022
11.00AM To 12.00PM
Strategic Partner
Research Partner
Overview
Organizations across industries are spending on AI/ML initiatives to generate business insights from data. But they are not able to scale their ML models to production at an enterprise level. Manual, time-consuming efforts are required for ML Model monitoring, ML Model retraining with new data and subsequent deployment to production environments. ML experiments are not reproducible, and Data Scientists do not have access to technical infrastructure that can auto- adapt to their needs. According to Gartner’s Top 10 Data and Analytics Technology Trends for 2020, 75% of companies will push their AI competitive frontiers by 2024. They will move away from pilot stage to scale AI adoption in production. Thus, organizations that are better prepared to channelize their AI investments in the appropriate Tools, Technologies, Practices, Frameworks and Skillsets will be better equipped to reap five-fold benefits in their ROI. Thus, organizations will need to solve the challenges arising from Poor Data Infrastructure
NASSCOM’s K-Tech Centre of Excellence for Data Science and Artificial Intelligence in association with Strategic Partner Genpact is launching the MLOps playbook, a compendium of MLOps implementation framework and industry best practices. The compendium incorporates extensive market research outcomes supported by EY as a ‘Research Partner’This playbook will be launched at the latest edition of AI Parley on 10th March, at 11:00 AM IST. In this edition, we will discuss about the MLOps landscape in India. The 45-minute virtual event will start with a welcome note, followed by the launch of the playbook and an engaging panel discussion with an eclectic panel The participants from across the globe will engage in an insightful panel discussion on the challenges of ML adoption at scale, need for MLOps to overcome the challenges and key drivers of MLOps adoption that can fuel the success stories of AI investments in organizations.