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Average Ratings 0 Ratings

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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 Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

ZenML Yes 

Integrations

ZenML No 

Pricing Details

$490 one-time fee
Per seat, available in packs of 5 seats
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

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 Yes 
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 Yes 

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 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 

Product Features

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 

Alternatives

Alternatives