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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

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 Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Google Cloud Platform Yes 
Kubernetes Yes 
APIFuzzer Yes 
Amazon Web Services (AWS) No 
Docker Yes 
GitHub No 
Google Colab No 
Gunicorn Yes 
Hugging Face No 
Jupyter Notebook No 
Kaggle No 
Microsoft Azure No 
OAuth Yes 
PyTorch No 
Python No 
R No 
TensorFlow No 
ZenML Yes 
pandas No 
scikit-learn No 

Integrations

Google Cloud Platform Yes 
Kubernetes Yes 
APIFuzzer No 
Amazon Web Services (AWS) Yes 
Docker No 
GitHub Yes 
Google Colab Yes 
Gunicorn No 
Hugging Face Yes 
Jupyter Notebook Yes 
Kaggle Yes 
Microsoft Azure Yes 
OAuth No 
PyTorch Yes 
Python Yes 
R Yes 
TensorFlow Yes 
ZenML No 
pandas Yes 
scikit-learn Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

$9 per month
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
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 No 
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 No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

ebhy

Website

github.com/ebhy/budgetml

Vendor Details

Company Name

DagsHub

Country

United States

Website

dagshub.com

Product Features

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