ProActive Workflows & Scheduling

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ProActive Workflows & Scheduling is a software that enables Job Scheduling, Workload Automation, Orchestration & Metascheduling on-premises and on all clouds.

ProActive Machine Learning

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ProActive Machine Learning (PML) from Activeeon is a data science automation platform that enables enterprises to: - Automate the complete data science lifecycle at scale, - Remove silos by creating a bridge between teams: DataOps, Data Science and DevOps, - Abstract application complexity by integrating all your favorite tools, - Abstract infrastructure complexity by connecting all your compute resources, - Allow easy communication between teams and unify the lifecycle. ProActive Machine Learning solution is designed to help you speed up the data science journey from extracting raw data to deploying models in production so that you can get the business advantages you are looking for. For data engineers: - Data connector tasks & workflows templates to automate and scale up data ingestion and data preparation pipelines. For data scientists: - AutoML to scale up the model tuning during experiments, - Jupyter Kernel & Python Connector to create AI workflows from code, - AI tasks & workflows template to automate AI pipelines to scale up parallel model training, validation and testing. For AI architects: - Model as a Service (MaaS) to deploy and expose AI models in production, enable model monitoring, alerting, data drift detection, scale up model deployment, - JupyterLab as a Service to deploy a JupyterLab instance on-demand, launch JupyterLab on specific compute nodes, - Job Analytics & Visualization as a Services to use your favorite tool to track and visualize metrics of your machine learning workflow, - Managed Services (KNIME, …) to launch your favorite tool on-demand.