Cognilytica’s Machine Learning Lifecycle for AI Virtual Conference was a three-day online experience held on January 26-28, 2021, focused on the machine learning lifecycle including ML Operations, building models, and model management.
Over the course of three days, the event combined live webinar-style panel engagements with pre-recorded presentations, opportunities to connect with speakers and sponsors through “ask-me-anything” style expert sessions, demo showcases, and unique experiences for attendees, speakers, sponsors, and all participants. The main focus areas were around government, technology and industry, and the main topic areas were on ML model development, ML model management, MLOps, ML model governance, and general sessions.
- ML model development
- ML model management
- ML Operations (MLOps)
- ML model governance
- All Other Topics Related to Digitization and Digitalization for AI
- Industry Applications
- Government and Public Sector Sessions
- Technology Deep Dives
Veritone was a key sponsor, watch and learn from our many informative sessions we hosted
Over the course of the week the event combined a large library of on-demand content with live keynotes and live webinar-style panel engagements, attendee/expert matching, “ask-me-anything” style expert sessions, and educational content.
Key topics include Data Engineering, Data Preparation, Data Labeling & Annotation, Sourcing Data and Data Generation for AI.
As a proud sponsor of the event, Veritone hosted 8 informative, content-rich sessions and an “Ask The Expert” session which are now available to view. Topics of each below will point you to the sessions that are right for you.
- The Ethical Side of Data Usage
- Building Trust in Your AI
- MLOps Done Right: Best Practices to Deploy. Integrate, Scale, Monitor, and Comply
- Using AI To Gain Insight Into Unstructured Data Trapped In Legacy Systems
- How AI is Helping Public Safety Agencies Demonstrate Greater Transparency
- Using Predictive AI to Optimize the Grid
- How AI Transforms Contact Centers in the Age of COVID
- Predictive Analytics And Data