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Description
Deep learning frameworks like TensorFlow, PyTorch, Caffe, Torch, Theano, and MXNet have significantly enhanced the accessibility of deep learning by simplifying the design, training, and application of deep learning models. Fabric for Deep Learning (FfDL, pronounced “fiddle”) offers a standardized method for deploying these deep-learning frameworks as a service on Kubernetes, ensuring smooth operation. The architecture of FfDL is built on microservices, which minimizes the interdependence between components, promotes simplicity, and maintains a stateless nature for each component. This design choice also helps to isolate failures, allowing for independent development, testing, deployment, scaling, and upgrading of each element. By harnessing the capabilities of Kubernetes, FfDL delivers a highly scalable, resilient, and fault-tolerant environment for deep learning tasks. Additionally, the platform incorporates a distribution and orchestration layer that enables efficient learning from large datasets across multiple compute nodes within a manageable timeframe. This comprehensive approach ensures that deep learning projects can be executed with both efficiency and reliability.
Description
Accelerate the development of your deep learning project on Google Cloud: Utilize Deep Learning Containers to swiftly create prototypes within a reliable and uniform environment for your AI applications, encompassing development, testing, and deployment phases. These Docker images are pre-optimized for performance, thoroughly tested for compatibility, and designed for immediate deployment using popular frameworks. By employing Deep Learning Containers, you ensure a cohesive environment throughout the various services offered by Google Cloud, facilitating effortless scaling in the cloud or transitioning from on-premises setups. You also enjoy the versatility of deploying your applications on platforms such as Google Kubernetes Engine (GKE), AI Platform, Cloud Run, Compute Engine, Kubernetes, and Docker Swarm, giving you multiple options to best suit your project's needs. This flexibility not only enhances efficiency but also enables you to adapt quickly to changing project requirements.
API Access
Has API
API Access
Has API
Integrations
Kubernetes
Caffe
Google Cloud Platform
Google Cloud Run
Google Compute Engine
Google Kubernetes Engine (GKE)
PyTorch
TensorFlow
Torch
Integrations
Kubernetes
Caffe
Google Cloud Platform
Google Cloud Run
Google Compute Engine
Google Kubernetes Engine (GKE)
PyTorch
TensorFlow
Torch
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
IBM
Founded
1911
Country
United States
Website
developer.ibm.com/open/projects/fabric-for-deep-learning-ffdl/
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/ai-platform/deep-learning-containers
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization