Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Caffe is a deep learning framework designed with a focus on expressiveness, efficiency, and modularity, developed by Berkeley AI Research (BAIR) alongside numerous community contributors. The project was initiated by Yangqing Jia during his doctoral studies at UC Berkeley and is available under the BSD 2-Clause license. For those interested, there is an engaging web image classification demo available for viewing! The framework’s expressive architecture promotes innovation and application development. Users can define models and optimizations through configuration files without the need for hard-coded elements. By simply toggling a flag, users can seamlessly switch between CPU and GPU, allowing for training on powerful GPU machines followed by deployment on standard clusters or mobile devices. The extensible nature of Caffe's codebase supports ongoing development and enhancement. In its inaugural year, Caffe was forked by more than 1,000 developers, who contributed numerous significant changes back to the project. Thanks to these community contributions, the framework remains at the forefront of state-of-the-art code and models. Caffe's speed makes it an ideal choice for both research experiments and industrial applications, with the capability to process upwards of 60 million images daily using a single NVIDIA K40 GPU, demonstrating its robustness and efficacy in handling large-scale tasks. This performance ensures that users can rely on Caffe for both experimentation and deployment in various scenarios.
Description
Berkeley DB encompasses a suite of embedded key-value database libraries that deliver scalable and high-performance data management functionalities for various applications. Its products utilize straightforward function-call APIs for accessing and managing data efficiently. With Berkeley DB, developers can create tailored data management solutions that bypass the typical complexities linked with custom projects. The library offers a range of reliable building-block technologies that can be adapted to meet diverse application requirements, whether for handheld devices or extensive data centers, catering to both local storage needs and global distribution, handling data volumes that range from kilobytes to petabytes. This versatility makes Berkeley DB a preferred choice for developers looking to implement efficient data solutions.
API Access
Has API
Yes
API Access
Has API
No
Integrations
AWS Elastic Fabric Adapter (EFA)
Yes
AWS Marketplace
Yes
Amazon Web Services (AWS)
Yes
BI Book
No
Checkmk
No
DashboardFox
No
Docker
Yes
Fabric for Deep Learning (FfDL)
Yes
JanusGraph
No
Ketch
No
Integrations
AWS Elastic Fabric Adapter (EFA)
No
AWS Marketplace
No
Amazon Web Services (AWS)
No
BI Book
Yes
Checkmk
Yes
DashboardFox
Yes
Docker
No
Fabric for Deep Learning (FfDL)
No
JanusGraph
Yes
Ketch
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
BAIR
Country
United States
Website
caffe.berkeleyvision.org
Vendor Details
Company Name
Oracle
Founded
1977
Country
United States
Website
www.oracle.com/database/technologies/related/berkeleydb.html
Product Features
Deep Learning
Convolutional Neural Networks
No
Document Classification
Yes
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
Yes
Product Features
NoSQL Database
Auto-sharding
Yes
Automatic Database Replication
Yes
Data Model Flexibility
Yes
Deployment Flexibility
Yes
Dynamic Schemas
Yes
Integrated Caching
Yes
Multi-Model
Yes
Performance Management
Yes
Security Management
Yes