Webinar: How to Deploy Your Hugging Face Model to Production at Scale - MLOps Live #20, Oct, 25 at 12pm ET
Meet the platform that automates MLOps and cuts the time to impact of your data science creations.
Ingest and unify unstructured and structured data in real-time and create online and offline features using Iguazio’s Integrated Feature Store.
Run experimentation over scalable serverless ML/DL runtimes with automated tracking, data versioning, and continuous integration/delivery (CI/CD) support.
Deploy models and APIs from a Jupyter notebook or IDE to production in just a few clicks and continuously monitor model performance and mitigate model drift.
Manage, govern and monitor your models and real-time features in production with a simple dashboard integrated with Iguazio’s Feature Store.
Engineer online and offline features with advanced data transformation.
Build and deploy automated real-time data and ML pipelines
Continuously develop and deploy models to production iteratively quickly and easily.
Easily monitor your models in production, automate drift detection to keep your models optimized and accurate in changing environments.
Manage your end to-end workflow to production using a user-friendly environment, featuring fully integrated workflow management, an integrated feature store and model monitoring
Build, train, optimize and automatically deploy from a serverless environment with managed services, whether it’s streaming, analytics, deep learning or event-driven apps
Easily engineer online and offline features, share them across teams and ML applications with minimal development and integration effort, on top of Iguazio’s real-time data engine
Accelerate the deployment and mangement of your AI applications with the Iguazio MLOps Platform