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What is UnionML?

Creating machine learning applications should be a smooth and straightforward process. UnionML is a Python-based open-source framework that builds upon Flyte™, simplifying the complex world of ML tools into a unified interface. It allows you to easily incorporate your preferred tools through a simple and standardized API, minimizing boilerplate code so you can focus on what truly counts: the data and the models that yield valuable insights. This framework makes it easier to merge a wide variety of tools and frameworks into a single protocol for machine learning. Utilizing established industry practices, you can set up endpoints for data collection, model training, prediction serving, and much more—all within one cohesive ML system. Consequently, data scientists, ML engineers, and MLOps experts can work together seamlessly using UnionML applications, creating a clear reference point for comprehending the dynamics of your machine learning architecture. This collaborative environment not only encourages innovation but also improves communication among team members, significantly boosting the overall productivity and success of machine learning initiatives. Ultimately, UnionML serves as a vital asset for teams aiming to achieve greater agility and productivity in their ML endeavors.

What is Tornado Web Server?

Tornado is a Python web framework that doubles as an asynchronous networking library, originally developed at FriendFeed. With its non-blocking network I/O, it can handle tens of thousands of concurrent connections, making it ideal for applications that rely on persistent user connections like long polling and WebSockets. Distinct from most Python web frameworks, Tornado does not adhere to the WSGI standard and typically functions on a single thread per process. While the tornado.wsgi module provides a degree of WSGI compatibility, it is not the primary focus of the framework’s development, and it is recommended that developers utilize Tornado’s dedicated interfaces, such as tornado.web, when creating applications. Additionally, it is crucial to understand that Tornado's code is generally not thread-safe. Since the release of version 5.0, Tornado has been integrated with Python's standard library asyncio module, allowing it to share the same default event loop. This integration facilitates the use of libraries built for asyncio alongside Tornado, significantly enhancing its versatility and overall functionality. Consequently, developers can construct highly efficient applications that harness both the strengths of Tornado and the capabilities of asyncio, leading to more robust and responsive user experiences. The adaptability of Tornado has made it a popular choice among developers who require high performance in their web applications.

Media

Media

Integrations Supported

Python
Amazon Web Services (AWS)
Google Cloud Platform
Microsoft Azure
New Relic
Swoole

Integrations Supported

Python
Amazon Web Services (AWS)
Google Cloud Platform
Microsoft Azure
New Relic
Swoole

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Union

Date Founded

2021

Company Location

United States

Company Website

www.union.ai/unionml

Company Facts

Organization Name

Tornado

Date Founded

2009

Company Location

United States

Company Website

www.tornadoweb.org/en/stable/

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Categories and Features

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