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EurekosEurekos is the customer training LMS built to educate the world outside your organization – partners, distributors, resellers and the networks beyond. Most companies spend years perfecting their product or service, then hand customers a repurposed employee training course and hope for the best. When those customers churn, the product gets the blame. Usually, the training is the problem. Eurekos fixes that. We help you turn training from a cost into a growth engine. The ability to sell courses, accreditations and learning paths directly through the platform doesn’t just help retain business. It transforms customer education into a revenue stream. The same thinking runs through the entire platform – in how Saga AI adapts every learning journey to the individual, in how training portals can be customized to different customers and regions, and in how we work with you long after you go live. Eurekos covers the entire customer journey – from pre-sales through onboarding to ongoing training, with everything you need to run a world-class external training operation. Certifications, eCommerce, unlimited branded portals, built-in content authoring and ISO/IEC 27001 & 27701-certified security. Eurekos Product Features: • Saga AI • Learning Journeys & Adaptive Paths • Built-in Course Authoring • Certification & Accreditation • Security & Compliance • Unlimited Branded Portals • eCommerce • Mobile Learning • Global Reach • Integrations & API
What is Amazon SageMaker Model Training?
Amazon SageMaker Model Training simplifies the training and fine-tuning of machine learning (ML) models at scale, significantly reducing both time and costs while removing the burden of infrastructure management. This platform enables users to tap into some of the cutting-edge ML computing resources available, with the flexibility of scaling infrastructure seamlessly from a single GPU to thousands to ensure peak performance. By adopting a pay-as-you-go pricing structure, maintaining training costs becomes more manageable. To boost the efficiency of deep learning model training, SageMaker offers distributed training libraries that adeptly spread large models and datasets across numerous AWS GPU instances, while also allowing the integration of third-party tools like DeepSpeed, Horovod, or Megatron for enhanced performance. The platform facilitates effective resource management by providing a wide range of GPU and CPU options, including the P4d.24xl instances, which are celebrated as the fastest training instances in the cloud environment. Users can effortlessly designate data locations, select suitable SageMaker instance types, and commence their training workflows with just a single click, making the process remarkably straightforward. Ultimately, SageMaker serves as an accessible and efficient gateway to leverage machine learning technology, removing the typical complications associated with infrastructure management, and enabling users to focus on refining their models for better outcomes.
What is Amazon SageMaker Feature Store?
Amazon SageMaker Feature Store is a specialized, fully managed storage solution created to store, share, and manage essential features necessary for machine learning (ML) models. These features act as inputs for ML models during both the training and inference stages. For example, in a music recommendation system, pertinent features could include song ratings, listening duration, and listener demographic data. The capacity to reuse features across multiple teams is crucial, as the quality of these features plays a significant role in determining the precision of ML models. Additionally, aligning features used in offline batch training with those needed for real-time inference can present substantial difficulties. SageMaker Feature Store addresses this issue by providing a secure and integrated platform that supports feature use throughout the entire ML lifecycle. This functionality enables users to efficiently store, share, and manage features for both training and inference purposes, promoting the reuse of features across various ML projects. Moreover, it allows for the seamless integration of features from diverse data sources, including both streaming and batch inputs, such as application logs, service logs, clickstreams, and sensor data, thereby ensuring a thorough approach to feature collection. By streamlining these processes, the Feature Store enhances collaboration among data scientists and engineers, ultimately leading to more accurate and effective ML solutions.
Integrations Supported
Amazon SageMaker
Amazon Web Services (AWS)
AWS Glue
AWS Lake Formation
Amazon Athena
Amazon Kinesis
Amazon Redshift
Amazon S3
Amazon SageMaker Data Wrangler
Amazon SageMaker Unified Studio
Integrations Supported
Amazon SageMaker
Amazon Web Services (AWS)
AWS Glue
AWS Lake Formation
Amazon Athena
Amazon Kinesis
Amazon Redshift
Amazon S3
Amazon SageMaker Data Wrangler
Amazon SageMaker Unified Studio
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/train/
Company Facts
Organization Name
Amazon
Date Founded
1994
Company Location
United States
Company Website
aws.amazon.com/sagemaker/feature-store/
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
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization