Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • RunPod Reviews & Ratings
    205 Ratings
    Company Website
  • Vertex AI Reviews & Ratings
    827 Ratings
    Company Website
  • Sage Intacct Reviews & Ratings
    7,935 Ratings
    Company Website
  • TrustInSoft Analyzer Reviews & Ratings
    6 Ratings
    Company Website
  • Fraud.net Reviews & Ratings
    56 Ratings
    Company Website
  • Google Cloud BigQuery Reviews & Ratings
    1,939 Ratings
    Company Website
  • FISPAN Reviews & Ratings
    5 Ratings
    Company Website
  • ManageEngine Log360 Reviews & Ratings
    141 Ratings
    Company Website
  • Google Compute Engine Reviews & Ratings
    1,155 Ratings
    Company Website
  • Flowlens Reviews & Ratings
    39 Ratings
    Company Website

What is Amazon SageMaker Debugger?

Improve machine learning models by capturing real-time training metrics and initiating alerts for any detected anomalies. To reduce both training time and expenses, the training process can automatically stop once the desired accuracy is achieved. Additionally, it is crucial to continuously evaluate and oversee system resource utilization, generating alerts when any limitations are detected to enhance resource efficiency. With the use of Amazon SageMaker Debugger, the troubleshooting process during training can be significantly accelerated, turning what usually takes days into just a few minutes by automatically pinpointing and notifying users about prevalent training challenges, such as extreme gradient values. Alerts can be conveniently accessed through Amazon SageMaker Studio or configured via Amazon CloudWatch. Furthermore, the SageMaker Debugger SDK is specifically crafted to autonomously recognize new types of model-specific errors, encompassing issues related to data sampling, hyperparameter configurations, and values that surpass acceptable thresholds, thereby further strengthening the reliability of your machine learning models. This proactive methodology not only conserves time but also guarantees that your models consistently operate at peak performance levels, ultimately leading to better outcomes and improved overall efficiency.

What is AWS IoT Core?

AWS IoT Core allows for a smooth connection between IoT devices and the AWS cloud, removing the complexities of server management and provisioning. It is designed to support a vast number of devices and an immense volume of messages, processing and routing them securely and reliably to both AWS endpoints and other interconnected devices. This service ensures continuous monitoring and communication with devices, even during offline periods. Moreover, AWS IoT Core enhances the integration of various AWS and Amazon services, including AWS Lambda, Amazon Kinesis, Amazon S3, Amazon SageMaker, Amazon DynamoDB, Amazon CloudWatch, AWS CloudTrail, Amazon QuickSight, and Alexa Voice Service, enabling developers to construct IoT applications that effectively handle data collection, processing, analysis, and response without worrying about infrastructure management. Additionally, its ability to connect an unlimited number of devices makes it a highly scalable and adaptable solution for a wide range of IoT scenarios. This flexibility supports innovation in smart technologies across different industries.

Media

Media

Integrations Supported

AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon Web Services (AWS)
AWS App Mesh
AWS CloudTrail
AWS IoT ExpressLink
Amazon DynamoDB
Amazon Kinesis
Amazon QuickSight
Amazon S3
Amazon SageMaker Unified Studio
Cogent DataHub
Everyware Software Framework (ESF)
FairCom DB
FairCom EDGE
Onomondo
Teal
TensorFlow

Integrations Supported

AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon Web Services (AWS)
AWS App Mesh
AWS CloudTrail
AWS IoT ExpressLink
Amazon DynamoDB
Amazon Kinesis
Amazon QuickSight
Amazon S3
Amazon SageMaker Unified Studio
Cogent DataHub
Everyware Software Framework (ESF)
FairCom DB
FairCom EDGE
Onomondo
Teal
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/debugger/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/iot-core/

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Categories and Features

IoT

Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization

IoT Analytics

Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking

Popular Alternatives

Popular Alternatives

Amazon MQ Reviews & Ratings

Amazon MQ

Amazon