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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
Bugsnag provides comprehensive monitoring of application stability, empowering teams to make informed choices about whether to prioritize the development of new features or to address existing bugs. As a robust full-stack stability monitoring solution tailored for mobile applications, it offers advanced diagnostics that enable you to replicate any error effectively. With a user-friendly interface, you can manage all your applications seamlessly from a single dashboard. Bugsnag serves as a crucial metric for assessing app health, facilitating communication between product and engineering teams. Not every bug requires immediate attention, allowing you to concentrate on those that significantly impact your business. Its extensible libraries come with well-considered defaults and a plethora of customization options. Additionally, the team comprises subject matter experts who are genuinely invested in minimizing errors and ensuring the overall health of your applications, making Bugsnag an invaluable asset for developers.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Amazon CloudWatch
Amazon SageMaker
Azure DevOps Server
CA Flowdock
Causal
DoneDone
Hitask
Josys
Netlify
Integrations
Amazon Web Services (AWS)
Amazon CloudWatch
Amazon SageMaker
Azure DevOps Server
CA Flowdock
Causal
DoneDone
Hitask
Josys
Netlify
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$59 per month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/sagemaker/debugger/
Vendor Details
Company Name
Bugsnag
Founded
2013
Country
United States
Website
www.bugsnag.com
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Product Features
Application Performance Monitoring (APM)
Baseline Manager
Diagnostic Tools
Full Transaction Diagnostics
Performance Control
Resource Management
Root-Cause Diagnosis
Server Performance
Trace Individual Transactions