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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

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.

Description

evoML enhances the efficiency of developing high-quality machine learning models by simplifying and automating the comprehensive data science process, enabling the conversion of raw data into meaningful insights in mere days rather than several weeks. It takes charge of vital tasks such as automatic data transformation that identifies anomalies and rectifies imbalances, employs genetic algorithms for feature engineering, conducts parallel evaluations of multiple model candidates, optimizes using multi-objective criteria based on custom metrics, and utilizes GenAI technology for generating synthetic data, which is especially useful for swift prototyping while adhering to data privacy regulations. Users maintain complete ownership of and can modify the generated model code, facilitating smooth deployment as APIs, databases, or local libraries, thereby preventing vendor lock-in and promoting clear, auditable workflows. Additionally, evoML equips teams with user-friendly visualizations, interactive dashboards, and detailed charts to detect patterns, outliers, and anomalies across various applications, including anomaly detection, time-series forecasting, and fraud prevention. With its robust features, evoML not only accelerates the modeling process but also empowers users to make data-driven decisions with confidence.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

ZenML

Integrations

ZenML

Pricing Details

$490 one-time fee
Free Trial
Free Version

Pricing Details

No price information available.
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

Explosion

Founded

2016

Country

Germany

Website

prodi.gy/

Vendor Details

Company Name

TurinTech AI

Founded

2018

Country

United Kingdom

Website

www.turintech.ai/evoml

Product Features

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Machine Learning

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

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Product Features

Machine Learning

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

Alternatives

Alternatives