Distributed ML Ops
Distributed Machine Learning Operations is very important for delivering Machine Learning Projects to our customers.
Overview
What is MLReef?
MLReef is a Machine Learning development platform that aims to democratize ML innovation across the entire organization.Distributed ML Development: - up to 5X in ML development throughput- up to 85% less dependency on internal data science capacity- Distributed workload on…
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What is MLReef?
MLReef is a Machine Learning development platform that aims to democratize ML innovation across the entire organization. Distributed ML Development: - up to 5X in ML development throughput - up to 85% less dependency on internal data science capacity - Distributed workload…
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- Setup fee optionalOptional
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- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
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Product Details
- About
- Integrations
- Competitors
- Tech Details
- Downloadables
What is MLReef?
MLReef is a Machine Learning development platform that aims to democratize ML innovation across the entire organization.
Distributed ML Development:
- up to 5X in ML development throughput
- up to 85% less dependency on internal data science capacity
- Distributed workload on complex data tasks with seamless involvable domain experts
- Higher acceptance of deploye models ad development is a joint task
Q: What is Distributed ML Development?
Distributed Machine Learning development is the process by which the value-added chain is structurally distributed to different actors across the organization to drive efficiency, transparency, quality and to democratize the knowledge and capacity to create Machine Learning.
Distributed ML Development:
- up to 5X in ML development throughput
- up to 85% less dependency on internal data science capacity
- Distributed workload on complex data tasks with seamless involvable domain experts
- Higher acceptance of deploye models ad development is a joint task
Q: What is Distributed ML Development?
Distributed Machine Learning development is the process by which the value-added chain is structurally distributed to different actors across the organization to drive efficiency, transparency, quality and to democratize the knowledge and capacity to create Machine Learning.
MLReef Features
- Supported: AI Modules: Create AI Modules from fully flexible Git repositories
- Supported: ML Pipelines: Empower everyone to participate in the ML value chain with low/no code
- Supported: Data Management: Make data processing a collaborative and connected work
- Supported: Experiment tracking: Run experiments iteratively and with full reproducibility
- Supported: Nautilus: Host MLReef on any infrastructure - on the cloud or on-premises
MLReef Screenshots
MLReef Video
Fast prototyping with MLReef (Tutorial!)
MLReef Integrations
MLReef Competitors
- cnvrg.io
- DataIku
- Clarifai
MLReef Technical Details
| Deployment Types | On-premise, Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Windows, Linux |
| Mobile Application | No |
| Supported Countries | Global |
| Supported Languages | English |
MLReef Downloadables
MLReef Customer Size Distribution
| Consumers | 40% |
|---|---|
| Small Businesses (1-50 employees) | 8% |
| Mid-Size Companies (51-500 employees) | 24% |
| Enterprises (more than 500 employees) | 28% |
