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Average Ratings 0 Ratings

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ease
features
design
support

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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

Deleaker is a powerful tool that detects memory leaks in C++,.NET and Delphi. It integrates seamlessly with Visual Studio and RAD Studio. It also works as a stand-alone app. Deleaker can identify and fix leaks such as memory leaks and GDI leaks. It also handles leaks in real-time. Debugging is easier with an intuitive interface, detailed reports and precise stack traces. Deleaker is a great tool for any project, big or small. It ensures that your software is efficient and leak-free.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Autodesk A360
C++Builder
Change Healthcare Data & Analytics
Delphi
Keras
MXNet
PyTorch
Qt Creator
TensorFlow
Visual Studio

Integrations

AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Autodesk A360
C++Builder
Change Healthcare Data & Analytics
Delphi
Keras
MXNet
PyTorch
Qt Creator
TensorFlow
Visual Studio

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$149
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

Softanics

Founded

2004

Country

Kyrgyzstan

Website

www.deleaker.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

Alternatives

Alternatives

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