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What is Horovod?

Horovod, initially developed by Uber, is designed to make distributed deep learning more straightforward and faster, transforming model training times from several days or even weeks into just hours or sometimes minutes. With Horovod, users can easily enhance their existing training scripts to utilize the capabilities of numerous GPUs by writing only a few lines of Python code. The tool provides deployment flexibility, as it can be installed on local servers or efficiently run in various cloud platforms like AWS, Azure, and Databricks. Furthermore, it integrates well with Apache Spark, enabling a unified approach to data processing and model training in a single, efficient pipeline. Once implemented, Horovod's infrastructure accommodates model training across a variety of frameworks, making transitions between TensorFlow, PyTorch, MXNet, and emerging technologies seamless. This versatility empowers users to adapt to the swift developments in machine learning, ensuring they are not confined to a single technology. As new frameworks continue to emerge, Horovod's design allows for ongoing compatibility, promoting sustained innovation and efficiency in deep learning projects.

What is Azure Data Science Virtual Machines?

Data Science Virtual Machines (DSVMs) are customized images of Azure Virtual Machines that are pre-loaded with a diverse set of crucial tools designed for tasks involving data analytics, machine learning, and artificial intelligence training. They provide a consistent environment for teams, enhancing collaboration and sharing while taking full advantage of Azure's robust management capabilities. With a rapid setup time, these VMs offer a completely cloud-based desktop environment oriented towards data science applications, enabling swift and seamless initiation of both in-person classes and online training sessions. Users can engage in analytics operations across all Azure hardware configurations, which allows for both vertical and horizontal scaling to meet varying demands. The pricing model is flexible, as you are only charged for the resources that you actually use, making it a budget-friendly option. Moreover, GPU clusters are readily available, pre-configured with deep learning tools to accelerate project development. The VMs also come equipped with examples, templates, and sample notebooks validated by Microsoft, showcasing a spectrum of functionalities that include neural networks using popular frameworks such as PyTorch and TensorFlow, along with data manipulation using R, Python, Julia, and SQL Server. In addition, these resources cater to a broad range of applications, empowering users to embark on sophisticated data science endeavors with minimal setup time and effort involved. This tailored approach significantly reduces barriers for newcomers while promoting innovation and experimentation in the field of data science.

Media

Media

Integrations Supported

Microsoft Azure
TensorFlow
Anaconda
Azure Blob Storage
Azure Databricks
Azure Machine Learning
Flyte
Jupyter Notebook
Keras
MLflow
MXNet
Microsoft 365
Microsoft Cognitive Toolkit
Microsoft Power BI
PyTorch
Python
SQL Server
VMware Cloud
easybooking JULIA

Integrations Supported

Microsoft Azure
TensorFlow
Anaconda
Azure Blob Storage
Azure Databricks
Azure Machine Learning
Flyte
Jupyter Notebook
Keras
MLflow
MXNet
Microsoft 365
Microsoft Cognitive Toolkit
Microsoft Power BI
PyTorch
Python
SQL Server
VMware Cloud
easybooking JULIA

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

$0.005
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Horovod

Company Website

horovod.ai/

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

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

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Categories and Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

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