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John Snow Labs - Annotation Lab

John Snow Labs - Annotation Lab

By: John Snow Labs Latest Version: Classifiers' Benchmark Info, Assign tasks to Project Owner:v440
Linux/Unix
Linux/Unix

Product Overview

Annotation Lab is a Free End-to-End No-Code platform for document labeling and AI/ML model training. It enables domain experts (e.g. nurses, doctors, lawyers, accountants, investors, etc.) to extract meaningful facts from text documents, images or PDFs and train models that will automatically predict those facts on new documents. This is done by using state-of-the-art Spark NLP pre-trained models or by tuning models to better handle specific use cases.

About the offer

Based on an auto-scaling architecture powered by Kubernetes, Annotation Lab can scale to many teams and projects. Enterprise-grade security is provided for free including support for air-gap environments, zero data sharing, role-based access, full audit trails, MFA, and identity provider integrations. It allows powerful experiments for model training and finetuning, model testing, and model deployment as API endpoints.
There is no limitation on the number of users, projects, tasks, models, or trainings that can be run with this subscription.

Healthcare and Visual features are available via BYOL.

Included Features:

  • Annotation support for Text, Image, Audio, Video and HTML content;
  • High productivity annotation UI with keyboard shortcuts and pre-annotations;
  • Support for text annotation in 250+ languages;
  • Out-of-the-box support for the following NLP tasks: Classification, Named Entity Recognition, Assertion Status, and Relation Extraction;
  • Support for projects and teams: 30+ project templates; unlimited projects and users, project import, export and cloning, project grouping;
  • Task assignment, tagging, and comments; duplicate tasks identification; task searching and filtering;
  • Consensus analysis and Inter Annotator Agreement charts;
  • Performance dashboards;
  • Enterprise-level security and privacy: role-based access control, role-based views, annotation versioning, full audit trail, Single Sign on;
  • AI-Assisted Annotation: never start from scratch but reuse existing models to pre-annotate tasks with the latest Spark NLP models for classification, NER, assertion status, and relation detection;
  • Full Models Hub integration: you can explore available models and embeddings, download them with the click of a button and reuse those in your project configuration.
  • Train Classification, NER, and Assertion Status models: use default parameters or easily tune them on the UI for different experiments;
  • Active Learning automatically trains new versions of your models once new annotations are available;
  • API access to all features for easy integration into custom data analysis pipelines;

Who is this offer for

  • Domain experts (e.g. nurses, doctors, lawyers, accountants, investors, etc.) who want to test DL models on their data or/and tune/train new models via an easy-to-use UI, without writing a line of code;
  • Data labeling teams who want to optimize the efficiency and speed of their day-to-day work with preannotations;
  • Data scientists who deal with NLP problems;
  • Machine Learning engineers who need to test/train/tune NLP models;
  • Scientific researcher groups who need to extract meaning from unstructured, natural language documents;
  • And anyone else interested in text and image analysis, image digitization, data extraction, document labeling and/or NLP model training.

Target verticals

The Annotation Lab is a domain-agnostic tool that can be used to annotate documents in any vertical. Its integration with the NLP Models Hub facilitates access to over 12k pre-trained models for general-purpose text documents and taxonomies.

When a Healthcare NLP license is available, the tool allows easy access and reuse of 550+ pre-trained models covering 400+ clinical and biomedical entity types.

Technical Specifications

  • Recommended memory: 32GB RAM
  • Recommended vCPU:8 vCPUs
  • Operating System:Ubuntu 20.04

3 Easy Steps to get started

  1. Subscribe to the product on the Azure Marketplace.

  2. Deploy it on a new machine.

  3. Access the login page for a guided experience on http://INSTANCE_IP. For the first login use the following credentials:

    • Username: admin
    • Password: INSTANCE_ID

Version

Classifiers' Benchmark Info, Assign tasks to Project Owner:v440

Operating System

Linux/Unix, Ubuntu 20.04

Delivery Methods

  • Amazon Machine Image

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