Shyft Score
Directory quality rating
68/100
Quiet
Found in 1 source
Our take
The verdict on mlop
AI-generated
Mlop offers experiment tracking for training ML models, helping data scientists and engineers manage and optimize their machine learning workflows.
Strengths
- Comprehensive experiment tracking
- Supports multiple ML frameworks
- AI readiness score of 75
Limitations
- Limited to ML model training
- Pricing not publicly disclosed
Best for: Data science teams focused on ML model training and optimization
Request a demo to evaluate mlop for your team.
See how mlop fits your stackAbout
What is mlop?
Experiment tracking for training ML models
Key capabilities
Version control for ML experiments
Real-time collaboration for data scientists
Automated reporting and visualization of results
Integration with popular ML frameworks
Customizable dashboards for tracking metrics
At a glance
Use cases
What you can do with mlop
track model training experiments
compare model performance
collaborate on ML projects
Best for
Data scientistsMachine learning engineersResearch teams
Pricing
mlop pricing
mlop starts at $29/mo
Starting at $29/mo
Ecosystem
Connected ecosystem
MCP servers, AI skills, and integrations that work with mlop
Integrations
TensorFlowPyTorchKubernetesJupyter NotebooksSlackGitHubAWS S3Google Cloud StorageAzure Machine Learning
FAQs
Frequently asked questions
Common questions about mlop and its capabilities
mlop pricing starts at $29/mo. Contact mlop for enterprise pricing and volume discounts.
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