Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Amazon SageMaker Model Training streamlines the process of training and fine-tuning machine learning (ML) models at scale, significantly cutting down both time and costs while eliminating the need for infrastructure management. Users can leverage top-tier ML compute infrastructure, benefiting from SageMaker’s capability to seamlessly scale from a single GPU to thousands, adapting to demand as necessary. The pay-as-you-go model enables more effective management of training expenses, making it easier to keep costs in check. To accelerate the training of deep learning models, SageMaker’s distributed training libraries can divide extensive models and datasets across multiple AWS GPU instances, while also supporting third-party libraries like DeepSpeed, Horovod, or Megatron for added flexibility. Additionally, you can efficiently allocate system resources by choosing from a diverse range of GPUs and CPUs, including the powerful P4d.24xl instances, which are currently the fastest cloud training options available. With just one click, you can specify data locations and the desired SageMaker instances, simplifying the entire setup process for users. This user-friendly approach makes it accessible for both newcomers and experienced data scientists to maximize their ML training capabilities.
Description
Specifically designed to deploy AI seamlessly across all types of data, our solution maximizes the potential of your unstructured information, enabling you to access, prepare, train, optimize, and implement AI without constraints. We have integrated our top-tier file and object storage options, such as PowerScale, ECS, and ObjectScale, with our PowerEdge servers and a contemporary, open data lakehouse framework. This combination empowers you to harness AI for your unstructured data, whether on-site, at the edge, or in any cloud environment, ensuring unparalleled performance and limitless scalability. Additionally, you can leverage a dedicated team of skilled data scientists and industry professionals who can assist in deploying AI applications that yield significant benefits for your organization. Moreover, safeguard your systems against cyber threats with robust software and hardware security measures alongside immediate threat detection capabilities. Utilize a unified data access point to train and refine your AI models, achieving the highest efficiency wherever your data resides, whether that be on-premises, at the edge, or in the cloud. This comprehensive approach not only enhances your AI capabilities but also fortifies your organization's resilience against evolving security challenges.
API Access
Has API
API Access
Has API
Integrations
AMD Radeon ProRender
Accenture AI Refinery
Amazon SageMaker
Amazon Web Services (AWS)
Apache Iceberg
BERT
Cloudera
CodeGPT
DALL·E 2
Dell EMC PowerScale
Integrations
AMD Radeon ProRender
Accenture AI Refinery
Amazon SageMaker
Amazon Web Services (AWS)
Apache Iceberg
BERT
Cloudera
CodeGPT
DALL·E 2
Dell EMC PowerScale
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
1994
Country
United States
Website
aws.amazon.com/sagemaker/train/
Vendor Details
Company Name
Dell
Founded
1984
Country
United States
Website
www.dell.com/en-us/dt/solutions/artificial-intelligence/storage-for-ai.htm
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization