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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.

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.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Businesses seeking a tool to optimize ML models with real-time monitoring of training metrics and system resources

Audience

High-performance ML teams

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

$100 + compute/month
Free Version
Free Trial

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
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Amazon
Founded: 1994
United States
aws.amazon.com/sagemaker/debugger/

Company Information

VESSL AI
Founded: 2020
United States
vessl.ai/

Alternatives

Alternatives

Categories

Categories

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
Llama 3.1
Llama 3.2
MXNet
Mixtral 8x7B
Pinecone
Stable Diffusion
TensorFlow
Visual Studio Code
Vultr

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
Llama 3.1
Llama 3.2
MXNet
Mixtral 8x7B
Pinecone
Stable Diffusion
TensorFlow
Visual Studio Code
Vultr
Claim Amazon SageMaker Debugger and update features and information
Claim Amazon SageMaker Debugger and update features and information
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