MLflow
Open-source platform for managing the machine learning lifecycle including experimentation and deployment.
MLOpsFree
4.7 (4321 reviews)
Key Features
- Experiment tracking
- Model registry
- Deployment
- Project packaging
- Model serving
- Open source
Pros
- Completely free
- Open source
- Databricks support
- Wide adoption
- Flexible deployment
- Good documentation
Cons
- Setup complexity
- UI limitations
- Self-hosted burden
- Scalability challenges
- Feature gaps
- Maintenance needs
Use Cases
Best For:
ML lifecycle managementOpen source projectsCustom deploymentsResearch teamsEnterprise ML
Not Recommended For:
Quick setupManaged solutionsSmall projectsNon-technical teams
Recent Reviews
John Developer
2 weeks ago
Excellent tool that has transformed our workflow. The API is well-documented and easy to integrate.
Sarah Tech
1 month ago
Great features but took some time to learn. Once you get the hang of it, it's incredibly powerful.
Mike Business
2 months ago
Best investment for our team. Increased productivity by 40% in just the first month.
Quick Info
CategoryMLOps
PricingFree
Rating4.7/5
Reviews4321
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