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Description

DSVMs, or Data Science Virtual Machines, are pre-configured Azure Virtual Machine images equipped with a variety of widely-used tools for data analysis, machine learning, and AI training. They ensure a uniform setup across teams, encouraging seamless collaboration and sharing of resources while leveraging Azure's scalability and management features. Offering a near-zero setup experience, these VMs provide a fully cloud-based desktop environment tailored for data science applications. They facilitate rapid and low-friction deployment suitable for both classroom settings and online learning environments. Users can execute analytics tasks on diverse Azure hardware configurations, benefiting from both vertical and horizontal scaling options. Moreover, the pricing structure allows individuals to pay only for the resources they utilize, ensuring cost-effectiveness. With readily available GPU clusters that come pre-configured for deep learning tasks, users can hit the ground running. Additionally, the VMs include various examples, templates, and sample notebooks crafted or validated by Microsoft, which aids in the smooth onboarding process for numerous tools and capabilities, including but not limited to Neural Networks through frameworks like PyTorch and TensorFlow, as well as data manipulation using R, Python, Julia, and SQL Server. This comprehensive package not only accelerates the learning curve for newcomers but also enhances productivity for seasoned data scientists.

Description

The RAPIDS software library suite, designed on CUDA-X AI, empowers users to run comprehensive data science and analytics workflows entirely on GPUs. It utilizes NVIDIA® CUDA® primitives for optimizing low-level computations while providing user-friendly Python interfaces that leverage GPU parallelism and high-speed memory access. Additionally, RAPIDS emphasizes essential data preparation processes tailored for analytics and data science, featuring a familiar DataFrame API that seamlessly integrates with various machine learning algorithms to enhance pipeline efficiency without incurring the usual serialization overhead. Moreover, it supports multi-node and multi-GPU setups, enabling significantly faster processing and training on considerably larger datasets. By incorporating RAPIDS, you can enhance your Python data science workflows with minimal code modifications and without the need to learn any new tools. This approach not only streamlines the model iteration process but also facilitates more frequent deployments, ultimately leading to improved machine learning model accuracy. As a result, RAPIDS significantly transforms the landscape of data science, making it more efficient and accessible.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Anaconda Yes 
Apache Spark Yes 
Capital One Spark Business Banking No 
Domino Enterprise AI Platform No 
Gradient No 
HPE Ezmeral Data Fabric No 
IBM Cloud No 
Iguazio No 
MLflow Yes 
Microsoft 365 Yes 
Microsoft Cognitive Toolkit Yes 
Microsoft Excel Yes 
Nuclio No 
Plotly Dash No 
SQL Server Yes 
TensorFlow Yes 
VMware Cloud Yes 
Visual Studio Yes 

Integrations

Anaconda Yes 
Apache Spark Yes 
Capital One Spark Business Banking Yes 
Domino Enterprise AI Platform Yes 
Gradient Yes 
HPE Ezmeral Data Fabric Yes 
IBM Cloud Yes 
Iguazio Yes 
MLflow No 
Microsoft 365 No 
Microsoft Cognitive Toolkit No 
Microsoft Excel No 
Nuclio Yes 
Plotly Dash Yes 
SQL Server No 
TensorFlow No 
VMware Cloud No 
Visual Studio No 

Pricing Details

$0.005
Free Trial Yes 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
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 Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

azure.microsoft.com/en-us/services/virtual-machines/data-science-virtual-machines/

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/rapids

Product Features

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

Product Features

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

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