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
VisualVM is a powerful tool used for monitoring and troubleshooting Java applications from version 1.4 onwards, supporting a variety of technologies such as jvmstat, JMX, Serviceability Agent (SA), and Attach API from different vendors. It is designed to meet the diverse needs of application developers, system administrators, quality engineers, and end users alike. For each running process, VisualVM displays essential runtime details including the process ID (PID), main class, arguments supplied to the Java process, JVM version, JDK home directory, JVM flags, and system properties. Additionally, it tracks various performance metrics such as CPU usage, garbage collection (GC) activity, heap and metaspace memory usage, the number of loaded classes, and the count of currently running threads. VisualVM also includes basic profiling features that allow for in-depth analysis of application performance and memory management, offering both sampling and instrumentation profiling options to cater to different analysis needs. This comprehensive set of tools makes VisualVM an invaluable resource for anyone looking to optimize their Java applications effectively.
API Access
Has API
No
API Access
Has API
No
Integrations
AWS Lambda
Yes
Amazon CloudWatch
Yes
Amazon SageMaker
Yes
Amazon SageMaker Studio
Yes
Amazon SageMaker Unified Studio
Yes
Amazon Web Services (AWS)
Yes
Change Healthcare Data & Analytics
Yes
Java
No
Keras
Yes
MXNet
Yes
Integrations
AWS Lambda
No
Amazon CloudWatch
No
Amazon SageMaker
No
Amazon SageMaker Studio
No
Amazon SageMaker Unified Studio
No
Amazon Web Services (AWS)
No
Change Healthcare Data & Analytics
No
Java
Yes
Keras
No
MXNet
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
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
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
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
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/sagemaker/debugger/
Vendor Details
Company Name
VisualVM
Website
visualvm.github.io
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