Amazon SageMaker DebuggerAmazon
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About
Optimize ML models by capturing training metrics in real-time and sending alerts when anomalies are detected. Automatically stop training processes when the desired accuracy is achieved to reduce the time and cost of training ML models. Automatically profile and monitor system resource utilization and send alerts when resource bottlenecks are identified to continuously improve resource utilization. Amazon SageMaker Debugger can reduce troubleshooting during training from days to minutes by automatically detecting and alerting you to remediate common training errors such as gradient values becoming too large or too small. Alerts can be viewed in Amazon SageMaker Studio or configured through Amazon CloudWatch. Additionally, the SageMaker Debugger SDK enables you to automatically detect new classes of model-specific errors such as data sampling, hyperparameter values, and out-of-bound values.
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About
Build, train, and deploy models faster at scale with fully managed infrastructure, tools, and workflows.
Deploy custom AI & LLMs on any infrastructure in seconds and scale inference with ease. Handle your most demanding tasks with batch job scheduling, only paying with per-second billing. Optimize costs with GPU usage, spot instances, and built-in automatic failover. Train with a single command with YAML, simplifying complex infrastructure setups. Automatically scale up workers during high traffic and scale down to zero during inactivity. Deploy cutting-edge models with persistent endpoints in a serverless environment, optimizing resource usage. Monitor system and inference metrics in real-time, including worker count, GPU utilization, latency, and throughput. Efficiently conduct A/B testing by splitting traffic among multiple models for evaluation.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Businesses seeking a tool to optimize ML models with real-time monitoring of training metrics and system resources
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Audience
High-performance ML teams
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
$100 + compute/month
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationAmazon
Founded: 1994
United States
aws.amazon.com/sagemaker/debugger/
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Company InformationVESSL AI
Founded: 2020
United States
vessl.ai/
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Categories |
Categories |
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Integrations
Amazon Web Services (AWS)
AWS Lambda
Amazon CloudWatch
Amazon SageMaker Studio
Change Healthcare Data & Analytics
FLUX.2
Gemma 2
Jupyter Notebook
Kubernetes
Llama 3
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Integrations
Amazon Web Services (AWS)
AWS Lambda
Amazon CloudWatch
Amazon SageMaker Studio
Change Healthcare Data & Analytics
FLUX.2
Gemma 2
Jupyter Notebook
Kubernetes
Llama 3
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