DVC

DVC

iterative.ai
+
+

Related Products

  • Gemini Enterprise Agent Platform
    4.3 out of 5 stars 1,178 Ratings
    Visit Website for Gemini Enterprise Agent Platform
  • Anaconda
    4.4 out of 5 stars 626 Ratings
    Visit Website for Anaconda
  • Runpod
    4.2 out of 5 stars 230 Ratings
    Visit Website for Runpod
  • IONOS Cloud GPU Servers
    4.6 out of 5 stars 45,816 Ratings
    Visit Website for IONOS Cloud GPU Servers
  • NINJIO
    4.8 out of 5 stars 416 Ratings
    Visit Website for NINJIO
  • Google Compute Engine
    4.4 out of 5 stars 1,169 Ratings
    Visit Website for Google Compute Engine
  • Total ETO
    4.6 out of 5 stars 46 Ratings
    Visit Website for Total ETO
  • Adzooma
    4.6 out of 5 stars 253 Ratings
    Visit Website for Adzooma
  • AnalyticsCreator
    4.6 out of 5 stars 46 Ratings
    Visit Website for AnalyticsCreator
  • Codemagic
    4.7 out of 5 stars 138 Ratings
    Visit Website for Codemagic

About

Data Version Control (DVC) is an open source version control system tailored for data science and machine learning projects. It offers a Git-like experience to organize data, models, and experiments, enabling users to manage and version images, audio, video, and text files in storage, and to structure their machine learning modeling process into a reproducible workflow. DVC integrates seamlessly with existing software engineering tools, allowing teams to define any aspect of their machine learning projects, data and model versions, pipelines, and experiments, in human-readable metafiles. This approach facilitates the use of best practices and established engineering toolsets, reducing the gap between data science and software engineering. By leveraging Git, DVC enables versioning and sharing of entire machine learning projects, including source code, configurations, parameters, metrics, data assets, and processes, by committing DVC metafiles as placeholders.

About

Declarative machine learning systems provide the best of flexibility and simplicity to enable the fastest-way to operationalize state-of-the-art models. Users focus on specifying the “what”, and the system figures out the “how”. Start with smart defaults, but iterate on parameters as much as you’d like down to the level of code. Our team pioneered declarative machine learning systems in industry, with Ludwig at Uber and Overton at Apple. Choose from our menu of prebuilt data connectors that support your databases, data warehouses, lakehouses, and object storage. Train state-of-the-art deep learning models without the pain of managing infrastructure. Automated Machine Learning that strikes the balance of flexibility and control, all in a declarative fashion. With a declarative approach, finally train and deploy models as quickly as you want.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Machine learning engineers wanting a tool to implement version control, reproducibility, and efficient collaboration in their projects

Audience

Declarative Machine Learning platform for organizations

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

Pay-as-you-go pricing
Free Version Not Supported
Free Trial Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Supported
Live Online Not Supported
In Person Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Supported
In Person Not Supported

Company Information

iterative.ai
Founded: 2018
United States
dvc.org

Company Information

Predibase
United States
predibase.com

Alternatives

Alternatives

Runpod

Runpod

4.2 out of 5 stars
Gemini Enterprise Agent Platform

Gemini Enterprise Agent Platform

Google
4.3 out of 5 stars
TensorFlow

TensorFlow

5.0 out of 5 stars

Categories

Categories

AI Development Supported
AI Fine-Tuning Supported
AI Infrastructure Supported
Machine Learning Supported

Integrations

Amazon Redshift Not Supported
Apache Hive Not Supported
Git Supported
LiteLLM Not Supported
MySQL Not Supported
Opik Not Supported
PostgreSQL Not Supported
Python Not Supported
Snowflake Not Supported
Truthlocks Supported
Visual Studio Code Supported

Integrations

Amazon Redshift Supported
Apache Hive Supported
Git Not Supported
LiteLLM Supported
MySQL Supported
Opik Supported
PostgreSQL Supported
Python Supported
Snowflake Supported
Truthlocks Not Supported
Visual Studio Code Not Supported
Claim DVC and update features and information
Claim DVC and update features and information
Claim Predibase and update features and information
Claim Predibase and update features and information