Getting Started with Experiment Management
We all know that machine learning is iterative, complex, and — at times — messy. Managing your experiments and automating the most tedious parts of the ML process are often the best place to start when it comes simplifying and making your job easier. This session will explore how experiment management can help you:
- Automatically track datasets, code changes, experimentation history and production models creating efficiency, transparency, and reproducibility – all at scale
- Standardize and track experiments across data science teams, even in large organizations
- Deliver custom visualizations and reports, to clearly communicate the results of your research
DataRobot is the leader in enterprise AI, delivering trusted AI technology and ROI enablement services to global enterprises. DataRobot’s enterprise AI platform democratizes data science with end-to-end automation for building, deploying, and managing machine learning models.
Production AI Model Management at Scale
Automate the standardized deployment, monitoring, governance, and validation of all your models to be developed in any environment. A single, production-grade environment for all your SAS, R, Machine Learning, and Regression model needs
Zorroa’s no-code ML integration platform makes process automations with machine learning APIs from GCP, AWS, and Azure accessible in under an hour. Its platform enables media technologists to stand up rapid-cycle experiments and scale their ML projects without code, data prep, or vendor lock-in.