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ease
features
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support

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Description

BudgetML is an ideal solution for professionals looking to swiftly launch their models to an endpoint without investing excessive time, money, or effort into mastering the complex end-to-end process. We developed BudgetML in response to the challenge of finding a straightforward and cost-effective method to bring a model into production promptly. Traditional cloud functions often suffer from memory limitations and can become expensive as usage scales, while Kubernetes clusters are unnecessarily complex for deploying a single model. Starting from scratch also requires navigating a myriad of concepts such as SSL certificate generation, Docker, REST, Uvicorn/Gunicorn, and backend servers, which can be overwhelming for the average data scientist. BudgetML directly addresses these hurdles, prioritizing speed, simplicity, and accessibility for developers. It is not intended for comprehensive production environments but serves as a quick and economical way to set up a server efficiently. Ultimately, BudgetML empowers users to focus on their models without the burden of unnecessary complications.

Description

DagsHub serves as a collaborative platform tailored for data scientists and machine learning practitioners to effectively oversee and optimize their projects. By merging code, datasets, experiments, and models within a cohesive workspace, it promotes enhanced project management and teamwork among users. Its standout features comprise dataset oversight, experiment tracking, a model registry, and the lineage of both data and models, all offered through an intuitive user interface. Furthermore, DagsHub allows for smooth integration with widely-used MLOps tools, which enables users to incorporate their established workflows seamlessly. By acting as a centralized repository for all project elements, DagsHub fosters greater transparency, reproducibility, and efficiency throughout the machine learning development lifecycle. This platform is particularly beneficial for AI and ML developers who need to manage and collaborate on various aspects of their projects, including data, models, and experiments, alongside their coding efforts. Notably, DagsHub is specifically designed to handle unstructured data types, such as text, images, audio, medical imaging, and binary files, making it a versatile tool for diverse applications. In summary, DagsHub is an all-encompassing solution that not only simplifies the management of projects but also enhances collaboration among team members working across different domains.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Google Cloud Platform
Kubernetes
APIFuzzer
Amazon Web Services (AWS)
Docker
FastAPI
GitHub
Google Colab
Hugging Face
Jupyter Notebook
Microsoft Azure
OAuth
PyTorch
Python
R
Swagger
TensorFlow
ZenML
pandas
scikit-learn

Integrations

Google Cloud Platform
Kubernetes
APIFuzzer
Amazon Web Services (AWS)
Docker
FastAPI
GitHub
Google Colab
Hugging Face
Jupyter Notebook
Microsoft Azure
OAuth
PyTorch
Python
R
Swagger
TensorFlow
ZenML
pandas
scikit-learn

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$9 per month
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

ebhy

Website

github.com/ebhy/budgetml

Vendor Details

Company Name

DagsHub

Country

United States

Website

dagshub.com

Product Features

Alternatives

Alternatives

Portkey Reviews

Portkey

Portkey.ai