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Description
We aim to transform the accessibility of production-ready Machine Learning. ZenML, a leading product in MAIOT, serves as an open-source MLOps framework that allows users to create reproducible Machine Learning pipelines. These pipelines are designed to manage the entire process from data versioning to deploying a model seamlessly. The framework’s core structure emphasizes extensible interfaces, enabling users to tackle intricate pipeline scenarios while also offering a user-friendly “happy path” that facilitates success in typical use cases without the burden of excessive boilerplate code. Our goal is to empower Data Scientists to concentrate on their specific use cases, objectives, and workflows related to Machine Learning, rather than on the complexities of the underlying technologies. As the landscape of Machine Learning rapidly evolves, both in software and hardware, we strive to separate reproducible workflows from the necessary tools, simplifying the integration of new technologies for users. Ultimately, this approach aims to foster innovation and streamline the development process in the Machine Learning realm.
Description
Revolutionary machine teaching is here with an exceptionally efficient annotation tool driven by active learning. Prodigy serves as a customizable annotation platform so effective that data scientists can handle the annotation process themselves, paving the way for rapid iteration. The advancements in today's transfer learning technologies allow for the training of high-quality models using minimal examples. By utilizing Prodigy, you can fully leverage contemporary machine learning techniques, embracing a more flexible method for data gathering. This will enable you to accelerate your workflow, gain greater autonomy, and deliver significantly more successful projects. Prodigy merges cutting-edge insights from the realms of machine learning and user experience design. Its ongoing active learning framework ensures that you only need to annotate those examples the model is uncertain about. The web application is not only powerful and extensible but also adheres to the latest user experience standards. The brilliance lies in its straightforward design: it encourages you to concentrate on one decision at a time, keeping you actively engaged – akin to a swipe-right approach for data. Additionally, this streamlined process fosters a more enjoyable and effective annotation experience overall.
API Access
Has API
No
API Access
Has API
Yes
Integrations
ZenML
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$490 one-time fee
Per seat, available in packs of 5 seats
Free Trial
No
Free Version
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
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
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
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
MAIOT
Founded
2021
Country
Germany
Website
www.maiot.io
Vendor Details
Company Name
Explosion
Founded
2016
Country
Germany
Website
prodi.gy/
Product Features
Fleet Maintenance
Cost Tracking
No
Fuel Tracking
No
Maintenance History
No
Maintenance Scheduling
No
Parts Inventory Management
No
Repair Tracking
No
Tire Management
No
Vehicle Information
No
Warranty Tracking
No
Work Order Management
No
Product Features
Data Labeling
Human-in-the-loop
No
Labeling Automation
Yes
Labeling Quality
No
Performance Tracking
No
Polygon, Rectangle, Line, Point
No
SDK
No
Supports Audio Files
No
Task Management
Yes
Team Collaboration
No
Training Data Management
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No
