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Description
Bayesforge™ is a specialized Linux machine image designed to assemble top-tier open source applications tailored for data scientists in need of sophisticated analytical tools, as well as for professionals in quantum computing and computational mathematics who wish to engage with key quantum computing frameworks. This image integrates well-known machine learning libraries like PyTorch and TensorFlow alongside open source tools from D-Wave, Rigetti, and platforms like IBM Quantum Experience and Google’s innovative quantum language Cirq, in addition to other leading quantum computing frameworks. For example, it features our quantum fog modeling framework and the versatile quantum compiler Qubiter, which supports cross-compilation across all significant architectures. Users can conveniently access all software through the Jupyter WebUI, which features a modular design that enables coding in Python, R, and Octave, enhancing flexibility in project development. Moreover, this comprehensive environment empowers researchers and developers to seamlessly blend classical and quantum computing techniques in their workflows.
Description
Quickly set up a virtual machine on Google Cloud for your deep learning project using the Deep Learning VM Image, which simplifies the process of launching a VM with essential AI frameworks on Google Compute Engine. This solution allows you to initiate Compute Engine instances that come equipped with popular libraries such as TensorFlow, PyTorch, and scikit-learn, eliminating concerns over software compatibility. Additionally, you have the flexibility to incorporate Cloud GPU and Cloud TPU support effortlessly. The Deep Learning VM Image is designed to support both the latest and most widely used machine learning frameworks, ensuring you have access to cutting-edge tools like TensorFlow and PyTorch. To enhance the speed of your model training and deployment, these images are optimized with the latest NVIDIA® CUDA-X AI libraries and drivers, as well as the Intel® Math Kernel Library. By using this service, you can hit the ground running with all necessary frameworks, libraries, and drivers pre-installed and validated for compatibility. Furthermore, the Deep Learning VM Image provides a smooth notebook experience through its integrated support for JupyterLab, facilitating an efficient workflow for your data science tasks. This combination of features makes it an ideal solution for both beginners and experienced practitioners in the field of machine learning.
API Access
Has API
No
API Access
Has API
No
Integrations
PyTorch
Yes
TensorFlow
Yes
AWS Marketplace
Yes
Chainer
No
D-Wave
Yes
Google Cirq
Yes
Google Cloud Platform
No
Google Cloud TPU
No
Google Compute Engine
No
IBM Quantum
Yes
Integrations
PyTorch
Yes
TensorFlow
Yes
AWS Marketplace
No
Chainer
Yes
D-Wave
No
Google Cirq
No
Google Cloud Platform
Yes
Google Cloud TPU
Yes
Google Compute Engine
Yes
IBM Quantum
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
Yes
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
No
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Quantum Programming Studio
Website
artiste-qb.net/bayesforge/
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/deep-learning-vm
Product Features
Product Features
Deep Learning
Convolutional Neural Networks
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
No