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Average Ratings 0 Ratings

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features
design
support

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Write a Review

Description

AWS IoT Core enables seamless connectivity between IoT devices and the AWS cloud, eliminating the need for server provisioning or management. Capable of accommodating billions of devices and handling trillions of messages, it ensures reliable and secure processing and routing of communications to AWS endpoints and other devices. This service empowers applications to continuously monitor and interact with all connected devices, maintaining functionality even during offline periods. Furthermore, AWS IoT Core simplifies the integration of various AWS and Amazon services, such as AWS Lambda, Amazon Kinesis, Amazon S3, Amazon SageMaker, Amazon DynamoDB, Amazon CloudWatch, AWS CloudTrail, Amazon QuickSight, and Alexa Voice Service, facilitating the development of IoT applications that collect, process, analyze, and respond to data from connected devices without the burden of infrastructure management. By utilizing AWS IoT Core, you can effortlessly connect an unlimited number of devices to the cloud and facilitate communication among them, streamlining your IoT solutions. This capability significantly enhances the efficiency and scalability of your IoT initiatives.

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.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS Lambda Yes 
Amazon CloudWatch Yes 
Amazon SageMaker Yes 
Amazon Web Services (AWS) Yes 
AWS App Mesh Yes 
AWS IoT ExpressLink Yes 
Amazon DynamoDB Yes 
Amazon QuickSight Yes 
Amazon SageMaker Studio No 
Amazon SageMaker Unified Studio No 
Equinix Smart View Yes 
Everyware Software Framework (ESF) Yes 
FairCom DB Yes 
FairCom EDGE Yes 
Keras No 
Onomondo Yes 
PyTorch No 
Teal Yes 
hopit Manufacturing Yes 

Integrations

AWS Lambda Yes 
Amazon CloudWatch Yes 
Amazon SageMaker Yes 
Amazon Web Services (AWS) Yes 
AWS App Mesh No 
AWS IoT ExpressLink No 
Amazon DynamoDB No 
Amazon QuickSight No 
Amazon SageMaker Studio Yes 
Amazon SageMaker Unified Studio Yes 
Equinix Smart View No 
Everyware Software Framework (ESF) No 
FairCom DB No 
FairCom EDGE No 
Keras Yes 
Onomondo No 
PyTorch Yes 
Teal No 
hopit Manufacturing 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 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 Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/iot-core/

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/sagemaker/debugger/

Product Features

IoT

Application Development No 
Big Data Analytics No 
Configuration Management No 
Connectivity Management No 
Data Collection No 
Data Management No 
Device Management No 
Performance Management No 
Prototyping No 
Visualization No 

IoT Analytics

Activity Dashboard No 
Activity Tracking No 
Analytics No 
Asset Tracking No 
Data Collection No 
Data Synchronization No 
Data Visualization No 
ETL No 
Multiple Data Sources No 
Performance Analysis No 
Real-Time Analytics No 
Real-Time Data No 
Real-Time Monitoring No 
Status Tracking No 

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 

Alternatives

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