Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Enhance machine learning model performance by capturing real-time training metrics and issuing alerts for any detected anomalies. To minimize both time and expenses associated with the training of ML models, the training processes can be automatically halted upon reaching the desired accuracy. Furthermore, continuous monitoring and profiling of system resource usage can trigger alerts when bottlenecks arise, leading to better resource management. The Amazon SageMaker Debugger significantly cuts down troubleshooting time during training, reducing it from days to mere minutes by automatically identifying and notifying users about common training issues, such as excessively large or small gradient values. Users can access alerts through Amazon SageMaker Studio or set them up via Amazon CloudWatch. Moreover, the SageMaker Debugger SDK further enhances model monitoring by allowing for the automatic detection of novel categories of model-specific errors, including issues related to data sampling, hyperparameter settings, and out-of-range values. This comprehensive approach not only streamlines the training process but also ensures that models are optimized for efficiency and accuracy.
Description
Proactively discover, predict, and resolve errors with the continuous code improvement platform.
API Access
Has API
No
API Access
Has API
Yes
Integrations
AWS Lambda
Yes
Amazon CloudWatch
Yes
Amazon SageMaker
Yes
Amazon SageMaker Unified Studio
Yes
Change Healthcare Data & Analytics
Yes
Cortex
No
GitHub
No
Indent
No
Jira
No
Jira Work Management
No
Integrations
AWS Lambda
No
Amazon CloudWatch
No
Amazon SageMaker
No
Amazon SageMaker Unified Studio
No
Change Healthcare Data & Analytics
No
Cortex
Yes
GitHub
Yes
Indent
Yes
Jira
Yes
Jira Work Management
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$19.00/month
Per month or Yearly pricing
Free Trial
Yes
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/sagemaker/debugger/
Vendor Details
Company Name
Rollbar
Founded
2012
Country
United States
Website
rollbar.com
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Product Features
Application Development
Access Controls/Permissions
Yes
Code Assistance
No
Code Refactoring
Yes
Collaboration Tools
Yes
Compatibility Testing
Yes
Data Modeling
Yes
Debugging
Yes
Deployment Management
Yes
Graphical User Interface
No
Mobile Development
No
No-Code
Yes
Reporting/Analytics
Yes
Software Development
No
Source Control
Yes
Testing Management
No
Version Control
No
Web App Development
No
Application Performance Monitoring (APM)
Baseline Manager
No
Diagnostic Tools
No
Full Transaction Diagnostics
No
Performance Control
No
Resource Management
No
Root-Cause Diagnosis
No
Server Performance
No
Trace Individual Transactions
No
Bug Tracking
Backlog Management
No
Filtering
No
Issue Tracking
Yes
Release Management
No
Task Management
No
Ticket Management
No
Workflow Management
No
Issue Tracking
Assignment Management
Yes
Dashboard
Yes
Escalation Management
Yes
Issue Auditing
Yes
Issue Scheduling
Yes
Knowledge Base
No
Project Management
Yes
Recurring Issues
Yes
Scheduling
No
Task Management
No