Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Data Version Control (DVC) is an open-source system specifically designed for managing version control in data science and machine learning initiatives. It provides a Git-like interface that allows users to systematically organize data, models, and experiments, making it easier to oversee and version various types of files such as images, audio, video, and text. This system helps structure the machine learning modeling process into a reproducible workflow, ensuring consistency in experimentation. DVC's integration with existing software engineering tools is seamless, empowering teams to articulate every facet of their machine learning projects through human-readable metafiles that detail data and model versions, pipelines, and experiments. This methodology promotes adherence to best practices and the use of well-established engineering tools, thus bridging the gap between the realms of data science and software development. By utilizing Git, DVC facilitates the versioning and sharing of complete machine learning projects, encompassing source code, configurations, parameters, metrics, data assets, and processes by committing the DVC metafiles as placeholders. Furthermore, its user-friendly approach encourages collaboration among team members, enhancing productivity and innovation within projects.
Description
Pachyderm's Data Versioning offers teams an efficient and automated method for monitoring all changes to their data. With file-based versioning, users benefit from a comprehensive audit trail that encompasses all data and artifacts at each stage of the pipeline, including intermediate outputs. The data is stored as native objects rather than mere metadata pointers, ensuring that versioning is both automated and reliable. The system can automatically scale by utilizing parallel processing for data without the need for additional coding. Incremental processing optimizes resource usage by only addressing the differences in data and bypassing any duplicates. Additionally, Pachyderm’s Global IDs simplify the tracking of results back to their original inputs, capturing all relevant analysis, parameters, code, and intermediate outcomes. The intuitive Pachyderm Console further enhances user experience by providing clear visualizations of the directed acyclic graph (DAG) and supports reproducibility through Global IDs, making it a valuable tool for teams managing complex data workflows. This comprehensive approach ensures that teams can confidently navigate their data pipelines while maintaining accuracy and efficiency.
API Access
Has API
No
API Access
Has API
No
Integrations
Determined AI
No
Git
Yes
Label Studio
No
Visual Studio Code
Yes
Integrations
Determined AI
Yes
Git
No
Label Studio
Yes
Visual Studio Code
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
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)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
iterative.ai
Founded
2018
Country
United States
Website
dvc.org
Vendor Details
Company Name
Pachyderm
Website
www.pachyderm.com
Product Features
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No