CaffeBAIR
|
||||||
Related Products
|
||||||
About
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Check out our web image classification demo! Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices. Extensible code fosters active development. In Caffe’s first year, it has been forked by over 1,000 developers and had many significant changes contributed back. Thanks to these contributors the framework tracks the state-of-the-art in both code and models. Speed makes Caffe perfect for research experiments and industry deployment. Caffe can process over 60M images per day with a single NVIDIA K40 GPU.
|
About
An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.
|
|||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||||
Audience
Anyone looking for an open-source deep learning framework with expression, speed and modularity
|
Audience
Organizations interested in a powerful open source machine learning platform
|
|||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||||
API
Offers API
|
API
Offers API
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
No information available.
Free Version
Free Trial
|
Pricing
Free
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationBAIR
United States
caffe.berkeleyvision.org
|
Company InformationTensorFlow
Founded: 2015
United States
www.tensorflow.org
|
|||||
Alternatives |
Alternatives |
|||||
|
|
|||||
|
|
|||||
|
||||||
|
|
|||||
Categories |
Categories |
|||||
Deep Learning Features
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
|
Machine Learning Features
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
|
|||||
Integrations
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Activeeon ProActive
Fabric for Deep Learning (FfDL)
Intel Tiber AI Studio
Lambda
NVIDIA DIGITS
OpenVINO
Polyaxon
Pop!_OS
|
Integrations
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Activeeon ProActive
Fabric for Deep Learning (FfDL)
Intel Tiber AI Studio
Lambda
NVIDIA DIGITS
OpenVINO
Polyaxon
Pop!_OS
|
|||||
|
|