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features
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support

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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

Models may be fleeting, but pipelines have a lasting presence. The cycle of training, evaluating, deploying, and repeating is essential. Valohai stands out as the sole MLOps platform that fully automates the entire process, from data extraction right through to model deployment. Streamline every aspect of this journey, ensuring that every model, experiment, and artifact is stored automatically. You can deploy and oversee models within a managed Kubernetes environment. Simply direct Valohai to your code and data, then initiate the process with a click. The platform autonomously launches workers, executes your experiments, and subsequently shuts down the instances, relieving you of those tasks. You can work seamlessly through notebooks, scripts, or collaborative git projects using any programming language or framework you prefer. The possibilities for expansion are limitless, thanks to our open API. Each experiment is tracked automatically, allowing for easy tracing from inference back to the original data used for training, ensuring full auditability and shareability of your work. This makes it easier than ever to collaborate and innovate effectively.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Git Yes 
Microsoft Azure No 
Visual Studio Code Yes 
WEKA No 

Integrations

Git No 
Microsoft Azure Yes 
Visual Studio Code No 
WEKA Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$560 per month
Free Trial Yes 
Free Version Yes 

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) Yes 
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 Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

iterative.ai

Founded

2018

Country

United States

Website

dvc.org

Vendor Details

Company Name

Valohai

Founded

2016

Country

Finland

Website

valohai.com

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics Yes 
Process/Workflow Automation Yes 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Deep Learning

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

Machine Learning

Deep Learning Yes 
ML Algorithm Library Yes 
Model Training Yes 
Natural Language Processing (NLP) No 
Predictive Modeling Yes 
Statistical / Mathematical Tools Yes 
Templates Yes 
Visualization Yes 

Predictive Analytics

AI / Machine Learning Yes 
Benchmarking Yes 
Data Blending No 
Data Mining No 
Demand Forecasting Yes 
For Education No 
For Healthcare No 
Modeling & Simulation Yes 
Sentiment Analysis No 

Alternatives

Alternatives

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