of data scientists time is spent on DevOps CNVRG.IO AI OS: • Code-first ML platform intelligently designed for data scientists • Multi-cloud/Hybrid-cloud and on-premise utilization with extensive resource management and cluster orchestration • One-click instant model deployment in scalable Kubernetes environment • Open container-based platform offers flexibility and control to use any image or tool • Fully customized, versioned, trackable, reusable, modular ML pipeline components of models don’t get to production AI:OS for Machine Learning Data Sheet 01 Monitoring cnvrg.io is an AI OS, transforming the way enterprises manage, scale and accelerate AI and data science development from research to production. The code-first platform is built by data scientists, for data scientists and offers unrivaled flexibility to run on-premises or cloud systems. From advanced MLOps to continual learning, cnvrg.io brings state of the art technology to data science teams so they can spend less time on DevOps and focus on the real magic - algorithms. Since using cnvrg.io, teams across industries have published more models to production resulting in increased business value. MONITOR RESEARCH DEPLOY EXPERIMENT DATASETS BUILD ACCELERATE ML WORKFLOWS WITH END-TO-END MLOPS OPERATIONALIZE ML MODELS IN PRODUCTION Focus less on technical complexity and more on building high impact ML models. cnvrg.io container-based infrastructure helps simplify engineering heavy tasks like tracking, monitoring, configuration, compute resource management, serving infrastructure, feature extraction, and model deployment. Instantly launch any ML or DL framework in one click with native integration to NVIDIA GPU-optimized Containers. Teams using cnvrg.io drastically reduce hidden technical debt, allowing data scientists to focus on productivity and increase business value. Deploy more models to production, and drive better business results. cnvrg.io packages your models for production in one click as a REST API endpoint leveraging Docker containers and your Kubernetes clusters. cnvrg.io users have full control of models in production with model versioning, advanced monitoring mechanisms and can control model performances over time. Deliver robust, production ready models with CI/CD integration, and apply advanced retraining triggers with human validation points in case of performance drift. Hidden Technical Debt in Machine Learning Systems D. Sculley, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips Configuration ML Code Serving Infrastructure Data Collection Analysis Tools Data Verification Feature Extraction Process Management Tools Machine Resource Management Monitoring 

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