What is BudgetML?

BudgetML provides an excellent option for practitioners who wish to quickly launch their models to an endpoint without the burden of extensive time, financial investment, or effort required to navigate the intricacies of complete deployment. The inspiration behind BudgetML arose from the challenges of locating an accessible and cost-effective approach for rapidly bringing a model into production. Using cloud functions can lead to issues with memory limitations and increased expenses when scaling, and Kubernetes clusters often introduce unnecessary complexity for the deployment of a single model. Starting from ground zero necessitates a grasp of various concepts like SSL certificate generation, Docker, REST APIs, Uvicorn/Gunicorn, and backend servers, which most data scientists may not be well-versed in. By addressing these challenges, BudgetML provides a solution that emphasizes speed, simplicity, and usability for developers. Although it may not cater to extensive production environments, BudgetML proves to be a valuable resource for quickly setting up a server at minimal expenses. In this way, BudgetML not only simplifies the deployment process but also allows data scientists to concentrate on refining their models rather than getting caught up in the complexities of deployment logistics. Ultimately, this makes BudgetML a practical choice for those looking to enhance their workflow and efficiency in model deployment.

Pricing

Price Starts At:
Free
Free Version:
Free Version available.

Integrations

Offers API?:
Yes, BudgetML provides an API

Screenshots and Video

BudgetML Screenshot 1

Company Facts

Company Name:
ebhy
Company Website:
github.com/ebhy/budgetml

Product Details

Deployment
SaaS
Training Options
Documentation Hub
Support
Web-Based Support

Product Details

Target Company Sizes
Individual
1-10
11-50
51-200
201-500
501-1000
1001-5000
5001-10000
10001+
Target Organization Types
Mid Size Business
Small Business
Enterprise
Freelance
Nonprofit
Government
Startup
Supported Languages
English

BudgetML Categories and Features