Determined AI vs. MLflow Comparison


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About Distributed training without changing your model code, determined takes care of provisioning machines, networking, data loading, and fault tolerance. Our open source deep learning platform enables you to train models in hours and minutes, not days and weeks. Instead of arduous tasks like manual hyperparameter tuning, re-running faulty jobs, and worrying about hardware resources. Our distributed training implementation outperforms the industry standard, requires no code changes, and is fully integrated with our state-of-the-art training platform. With built-in experiment tracking and visualization, Determined records metrics automatically, makes your ML projects reproducible and allows your team to collaborate more easily. Your researchers will be able to build on the progress of their team and innovate in their domain, instead of fretting over errors and infrastructure.	About MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects.
Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Companies looking for an open source deep learning training platform that makes building models fast and easy	Audience Companies looking for an open source platform solution for the machine learning lifecycle
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Not Supported	API Offers API Supported
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Pricing No information available. Free Version Not Supported Free Trial Not Supported	Pricing No information available. Free Version Not Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information Determined AI United States www.determined.ai/	Company Information MLflow Founded: 2018 United States mlflow.org
Alternatives Comet	Alternatives Union Cloud Union.ai
Gemini Enterprise Agent Platform Google	Amazon SageMaker Amazon
ClearML	ClearML
Ray Anyscale	Azure Machine Learning Microsoft
TensorFlow View All	DVC iterative.ai View All
Categories AI Development Supported Artificial Intelligence Supported Deep Learning Supported ML Experiment Tracking Supported	Categories AI Gateways Supported LLM Evaluation Supported Machine Learning Supported ML Experiment Tracking Supported ML Model Deployment Supported ML Model Management Supported

Integrations Amazon SageMaker Supported Apache Spark Supported Google Cloud Platform Supported TensorFlow Supported Apolo Not Supported Aporia Not Supported Databricks Not Supported Determined AI Not Supported Hadoop Supported Kedro Not Supported Keras Not Supported Kubernetes Not Supported OpenMetadata Not Supported Ragas Not Supported TrueFoundry Not Supported UbiOps Not Supported lakeFS Not Supported neptune.ai Not Supported Show More Integrations View All 11 Integrations	Integrations Amazon SageMaker Supported Apache Spark Supported Google Cloud Platform Supported TensorFlow Supported Apolo Supported Aporia Supported Databricks Supported Determined AI Supported Hadoop Not Supported Kedro Supported Keras Supported Kubernetes Supported OpenMetadata Supported Ragas Supported TrueFoundry Supported UbiOps Supported lakeFS Supported neptune.ai Supported Show More Integrations View All 47 Integrations
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