Caffe

Caffe

BAIR
+
+

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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/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

BAIR
United States
caffe.berkeleyvision.org

Company Information

TensorFlow
Founded: 2015
United States
www.tensorflow.org

Alternatives

MXNet

MXNet

The Apache Software Foundation

Alternatives

DeepSpeed

DeepSpeed

Microsoft

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
Fabric for Deep Learning (FfDL)
Lambda
NVIDIA DIGITS
OpenVINO
Polyaxon
Pop!_OS
Zebra by Mipsology
AUSIS
Azure Data Science Virtual Machines
Clore.ai
Deep Lake
Magenta Studio
NVIDIA FLARE
Runyour AI
Sesterce
Tecton

Integrations

AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Fabric for Deep Learning (FfDL)
Lambda
NVIDIA DIGITS
OpenVINO
Polyaxon
Pop!_OS
Zebra by Mipsology
AUSIS
Azure Data Science Virtual Machines
Clore.ai
Deep Lake
Magenta Studio
NVIDIA FLARE
Runyour AI
Sesterce
Tecton
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