Accelerate Concept to Value: Human Centric Design driven ML Ops
Sign up for the Pactera 1:1 Ask an Expert Session Despite the promise of AI, 90% of data science initiatives fail to achieve adoption and
Machine Learning Lifecycle 2021 Conference
Cognilytica’s Machine Learning Lifecycle Virtual Conference is a three day online experience January 26-28, 2021 focused on the machine learning lifecycle including ML Operations, building models, and model management!
January 26, 2021
Machine Learning Lifecycle 2021 Conference
Cognilytica’s Machine Learning Lifecycle Virtual Conference is a three day online experience January 26-28, 2021 focused on the machine learning lifecycle including ML Operations, building models, and model management! We've found virtual conferences that try to recreate the experience of in-person events really miss the mark. Cognilytica's Machine Learning Lifecycle for AI Conference is different - and so much better! Over the course of three days the event will combine 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.
Content is meant to be consumed around your schedule, not a predetermined schedule created for you. Main focus areas are around government, technology, and industry and main topic areas will be on ML model development, ML model management, MLOps, ML model governance, and general sessions.
WHERE: Online
WHEN: Tuesday through Thursday, Jan. 26-28, 2021
HOW MUCH: FREE to Attend
Five Topics:
- ML Model Development
- ML Model Management
- ML Operations (MLOps)
- ML Model Governance
- All other Model-related Topics
Three Tracks:
- Industry Applications
- Government and Public Sector Sessions
- Technology Deep Dives
View Sessions
Accelerating AI Adoption with Machine Learning Operations (MLOps)
Massive investments in data science teams and machine learning platforms have yet to yield results for most companies. The last mile for AI project success
Accelerating innovation with the latest ML APIs
While the move to pre-trained ML models eliminates the need to train a neural network from scratch, integrating it into your app or workflow still
AI and Data Governance: State CDO Perspectives
In this interactive panel hear from State Chief Data Officers (CDOs) on their perspectives on AI and data governance.
AI applications for Healthcare Economics
With increased prevalence of AI being applied to healthcare, there is a tremendous opportunity in transforming and improving Healthcare Economics tagged with patient care, provider
AI Governance: Your Path to Regulatory excellence
Leading organizations are implementing ML/AI to optimize processes and production, increase revenue, and reduce cost and risks. Success depends on AI governance to meet compliance
AI in Healthcare (Panel)
In this panel, we hear how leading healthcare industry professionals are tackling the challenges of healthcare with AI.
AI in Turbulent Times: New world, old model. Now what?
The world is changing around us, and deployed machine learning models are losing their power as current behaviors in the economy shift and change rapidly
Analytics Strategy of a 21st Century Insurance Company
There is no doubt about the impact of predictive analytics in any insurance company – large, medium, or small. The question that everyone is asking:
Are you using Airflow or similar SW for ML pipelining? You’re doing it all wrong.
There are many that try to bridge the gap between the iterative, incremental work done in Research and the integrated, routinely automated workflows of modern
Automated Machine Learning 101: Is Your Company Ready?
According to an O’Reilly study on AI adoption in the enterprise, 19 percent of respondents said they work for companies that plan to spend at
Automated Machine Learning in Action
Machine learning dramatically improves decision making via sophisticated predictive analytics that learns patterns from historical data. Led by Data Scientists, predictive analytics is enabling companies
Presenters & Panelists
Dewayne Whitfield
Technology Product and Innovation Strategist, US Postal Service (Former)
