On-demand webinar with Microsoft & Github: Git-Based CI / CD for Machine Learning & MLOps
Meet the platform that automates and accelerates complete machine learning workflows, cutting the time to impact of your data science creations.
Ingest in real-time multi-model data at scale, including event-driven streaming, time series, NoSQL, SQL and files.
Explore and manipulate online and offline data at scale, powered by Iguazio's real-time data layer and using your favorite data science and analytics frameworks, already pre-installed in the platform.
Continuously train models in a production-like environment, dynamically scaling GPUs and managed machine learning frameworks.
Deploy models and APIs from a Jupyter notebook or IDE to production in just a few clicks and continuously monitor model performance.
Streamline the process of data preparation, training, validation and deployment to operationalize your models with Kubeflow integration
Automatically track code, metadata, inputs and outputs of executions with MLRun and easily reproduce results
Run multiple experiments in parallel and automatically select the best result
Manage your workflow end to-end using a user-friendly environment, featuring fully integrated workflow management, experiment tracking and AutoML tools
Build, train, optimize and automatically deploy from a serverless environment with managed services, whether it’s streaming, analytics, deep learning or event-driven apps
Normalize, access, explore and manipulate fresh and historical data of all types, including event-driven streaming, time series, NoSQL, SQL and files at the highest performance