DVC

DVC

iterative.ai
Ray

Ray

Anyscale
+
+

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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

Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

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

Audience

ML and AI Engineers, Software Developers

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

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
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

iterative.ai
Founded: 2018
United States
dvc.org

Company Information

Anyscale
Founded: 2019
United States
ray.io

Alternatives

Alternatives

Vertex AI

Vertex AI

Google
AWS Neuron

AWS Neuron

Amazon Web Services
Keepsake

Keepsake

Replicate

Categories

Categories

Integrations

Amazon EC2 Trn2 Instances
Amazon EKS
Amazon SageMaker
Anyscale
Apache Airflow
Azure Kubernetes Service (AKS)
Dask
Databricks Data Intelligence Platform
Feast
Flyte
Git
Google Cloud Platform
Kubernetes
LanceDB
MLflow
PyTorch
Python
Union Cloud
Visual Studio Code
io.net

Integrations

Amazon EC2 Trn2 Instances
Amazon EKS
Amazon SageMaker
Anyscale
Apache Airflow
Azure Kubernetes Service (AKS)
Dask
Databricks Data Intelligence Platform
Feast
Flyte
Git
Google Cloud Platform
Kubernetes
LanceDB
MLflow
PyTorch
Python
Union Cloud
Visual Studio Code
io.net
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