|
gptkbp:instance_of
|
gptkb:software
|
|
gptkbp:developed_by
|
gptkb:Intel_Corporation
|
|
gptkbp:enables
|
Real-time inference
Scalable deployment
Model compression
|
|
gptkbp:enhances
|
Performance of AI models
|
|
gptkbp:facilitates
|
Edge deployment
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Intel Deep Learning Deployment Toolkit
|
|
gptkbp:includes
|
gptkb:Open_VINO_toolkit
|
|
gptkbp:integrates_with
|
gptkb:Kubernetes
gptkb:Docker
|
|
gptkbp:is_available_on
|
gptkb:Git_Hub
Intel website
|
|
gptkbp:is_compatible_with
|
gptkb:Linux
gptkb:Intel_architecture
gptkb:mac_OS
gptkb:Windows
|
|
gptkbp:is_designed_for
|
Research purposes
Enterprise applications
Production environments
|
|
gptkbp:is_optimized_for
|
Intel hardware
|
|
gptkbp:is_part_of
|
gptkb:ecosystem
Intel AI portfolio
AI model lifecycle
|
|
gptkbp:is_used_by
|
Data scientists
Machine learning engineers
|
|
gptkbp:is_used_in
|
gptkb:Retail
Automotive
Finance
Healthcare
Manufacturing
|
|
gptkbp:offers
|
gptkb:Community_support
Performance benchmarks
Performance tuning tools
|
|
gptkbp:provides
|
gptkb:Documentation
gptkb:user_interface
Pre-trained models
Sample applications
Performance profiling tools
Model optimization
Inference engine
|
|
gptkbp:purpose
|
Deploy deep learning models
|
|
gptkbp:released_in
|
gptkb:2018
|
|
gptkbp:supports
|
gptkb:Tensor_Flow
gptkb:MXNet
gptkb:Py_Torch
Batch processing
Transfer learning
Multi-platform deployment
Model serving
Federated learning
Model quantization
Model pruning
Streaming inference
|
|
gptkbp:utilizes
|
gptkb:Intel_GPUs
gptkb:Intel_FPGAs
gptkb:Intel_CPUs
|
|
gptkbp:bfsParent
|
gptkb:Intel_Performance_Libraries
|
|
gptkbp:bfsLayer
|
6
|