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
Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data processing and model training into a single pipeline. Once Horovod has been configured, the same infrastructure can be used to train models with any framework, making it easy to switch between TensorFlow, PyTorch, MXNet, and future frameworks as machine learning tech stacks continue to evolve.
|
|||||
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
Developers in need of a powerful Development Framework solution
|
|||||
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 InformationHorovod
horovod.ai/
|
|||||
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
|
||||||
Integrations
Activeeon ProActive
Amazon Web Services (AWS)
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Azure Databricks
Docker
Fabric for Deep Learning (FfDL)
Flyte
Intel Tiber AI Studio
Keras
|
Integrations
Activeeon ProActive
Amazon Web Services (AWS)
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Azure Databricks
Docker
Fabric for Deep Learning (FfDL)
Flyte
Intel Tiber AI Studio
Keras
|
|||||
|
|