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What is Cyber Train?

Sage Cyber Train functions as an all-encompassing Training Management System (TMS) that provides the necessary flexibility to manage and deliver educational materials while streamlining and automating administrative tasks. The platform integrates effortlessly with Sage HRMS and various HR systems, offering single-sign-on access to the Applicant Tracking solution, Sage Cyber Recruiter. By serving as a centralized, on-demand resource for corporate learning and development, Sage Cyber Train significantly improves the educational experience for users. With adaptable deployment options available, whether on-premise or in the cloud, it promotes an efficient learning atmosphere that effectively tracks and oversees progress. Moreover, it empowers users to curate and share diverse course materials, facilitating the development of customized curricula and the management of certification programs tailored to the unique needs of organizations. This system not only enhances hiring efficiency but also elevates the candidate experience by automating the entire recruiting and onboarding process. Consequently, these features allow organizations to prioritize their growth while upholding exceptional standards in both training and recruitment. Ultimately, Sage Cyber Train positions itself as an essential tool for businesses aiming to cultivate a skilled workforce.

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.

Media

Media

Integrations Supported

AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Change Healthcare Data & Analytics
Keras
MXNet
PyTorch
TensorFlow

Integrations Supported

AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Change Healthcare Data & Analytics
Keras
MXNet
PyTorch
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

Visibility Software

Date Founded

1999

Company Location

United States

Company Website

go.visibilitysoftware.com/training

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/debugger/

Categories and Features

Training

Academic / Education
Asynchronous Learning
Blended Learning
Built-In Course Authoring
Built-in LMS
Certification Management
Corporate / Business
Learner Portal
Mobile Learning
Simulation
Synchronous Learning
Training Companies
eCommerce

Categories and Features

Machine Learning

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

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