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Average Ratings 0 Ratings
Description
Amazon Elastic Inference provides an affordable way to enhance Amazon EC2 and Sagemaker instances or Amazon ECS tasks with GPU-powered acceleration, potentially cutting deep learning inference costs by as much as 75%. It is compatible with models built on TensorFlow, Apache MXNet, PyTorch, and ONNX. The term "inference" refers to the act of generating predictions from a trained model. In the realm of deep learning, inference can represent up to 90% of the total operational expenses, primarily for two reasons. Firstly, GPU instances are generally optimized for model training rather than inference, as training tasks can handle numerous data samples simultaneously, while inference typically involves processing one input at a time in real-time, resulting in minimal GPU usage. Consequently, relying solely on GPU instances for inference can lead to higher costs. Conversely, CPU instances lack the necessary specialization for matrix computations, making them inefficient and often too sluggish for deep learning inference tasks. This necessitates a solution like Elastic Inference, which optimally balances cost and performance in inference scenarios.
Description
Amazon SageMaker Canvas democratizes access to machine learning by equipping business analysts with an intuitive visual interface that enables them to independently create precise ML predictions without needing prior ML knowledge or coding skills. This user-friendly point-and-click interface facilitates the connection, preparation, analysis, and exploration of data, simplifying the process of constructing ML models and producing reliable predictions. Users can effortlessly build ML models to conduct what-if scenarios and generate both individual and bulk predictions with minimal effort. The platform enhances teamwork between business analysts and data scientists, allowing for the seamless sharing, reviewing, and updating of ML models across different tools. Additionally, users can import ML models from various sources and obtain predictions directly within Amazon SageMaker Canvas. With this tool, you can draw data from diverse origins, specify the outcomes you wish to forecast, and automatically prepare as well as examine your data, enabling a swift and straightforward model-building experience. Ultimately, this capability allows users to analyze their models and yield accurate predictions, fostering a more data-driven decision-making culture across organizations.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Amazon EC2
Amazon EC2 G4 Instances
Amazon SageMaker
Amazon SageMaker Unified Studio
MXNet
PyTorch
TensorFlow
Integrations
Amazon Web Services (AWS)
Amazon EC2
Amazon EC2 G4 Instances
Amazon SageMaker
Amazon SageMaker Unified Studio
MXNet
PyTorch
TensorFlow
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
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
2006
Country
United States
Website
aws.amazon.com/machine-learning/elastic-inference/
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/sagemaker/ai/canvas/
Product Features
Infrastructure-as-a-Service (IaaS)
Analytics / Reporting
Configuration Management
Data Migration
Data Security
Load Balancing
Log Access
Network Monitoring
Performance Monitoring
SLA Monitoring
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization