CaffeBAIR
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Related Products
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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.
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About
Steev is an AI training assistant that manages your training runs, eliminating the need for constant supervision and enhancing model performance. It reviews and analyzes your code before training begins, identifying potential errors, providing fixes, and suggesting better approaches to improve your workflow and outcomes. Steev takes proactive steps, adjusts training parameters, and resolves issues before they escalate, going beyond mere observation. Tracking all key variables during training, Steev sends instant notifications when your attention is needed, eliminating constant progress checks. Everything you need for smarter training is built into Steev, ready to go with zero setup required. You can try Steev for free during their beta program.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Anyone looking for an open-source deep learning framework with expression, speed and modularity
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Audience
Machine learning engineers seeking an automated solution to optimize and monitor their model training processes, reducing manual oversight and improving efficiency
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationBAIR
United States
caffe.berkeleyvision.org
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Company InformationSteev
United States
www.steev.io
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Alternatives |
Alternatives |
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Categories |
Categories |
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Deep Learning Features
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
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Integrations
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon Web Services (AWS)
Docker
Fabric for Deep Learning (FfDL)
Lambda
NVIDIA DIGITS
OpenVINO
Polyaxon
Pop!_OS
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Integrations
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon Web Services (AWS)
Docker
Fabric for Deep Learning (FfDL)
Lambda
NVIDIA DIGITS
OpenVINO
Polyaxon
Pop!_OS
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