Encord

Data Analysis AI Tool

Encord Active is a tool for machine learning and computer vision developers. It primarily focuses on model evaluation, data curation and active learning. This tool allows users to effectively test, validate, and fine-tune AI models against their data sets to significantly enhance model performance. With Encord Active, the users are able to run robustness checks on their AI models before deploying them into production. It provides advanced analytics, allowing users to spot and fix model weak spots, thus maintaining accurate and adaptable models even as data landscapes change. Furthermore, they can uncover model failure modes, export explainability reports, and quickly rectify issues, thus surpassing their AI benchmarks. The tool is also engineered for data and label validation, assisting developers to safeguard the quality of their training data. Encord Active's advanced label validation features boost the accuracy and reliability of the training data. It supports creation of balanced, comprehensive datasets tailored to the model's needs and automatically detects label errors through AI-assisted quality metrics. The system also allows developers to inspect model predictions, surface common issues, and efficiently communicate errors back to the labeling team. As a result, Encord Active helps facilitate quicker and more efficient deployment of high-quality AI applications in production.

About Encord

Encord Active is a tool for machine learning and computer vision developers. It primarily focuses on model evaluation, data curation and active learning. This tool allows users to effectively test, validate, and fine-tune AI models against their data sets to significantly enhance model performance. With Encord Active, the users are able to run robustness checks on their AI models before deploying them into production. It provides advanced analytics, allowing users to spot and fix model weak spots, thus maintaining accurate and adaptable models even as data landscapes change. Furthermore, they can uncover model failure modes, export explainability reports, and quickly rectify issues, thus surpassing their AI benchmarks. The tool is also engineered for data and label validation, assisting developers to safeguard the quality of their training data. Encord Active's advanced label validation features boost the accuracy and reliability of the training data. It supports creation of balanced, comprehensive datasets tailored to the model's needs and automatically detects label errors through AI-assisted quality metrics. The system also allows developers to inspect model predictions, surface common issues, and efficiently communicate errors back to the labeling team. As a result, Encord Active helps facilitate quicker and more efficient deployment of high-quality AI applications in production.

Key Features

  • ✅ Advanced active learning toolkit
  • ✅ Automatic label error detection
  • ✅ Natural language search for data
  • ✅ Debugging and performance enhancement capabilities
  • ✅ Detailed dataset impact breakdown
  • ✅ Customizable metrics integration
  • ✅ Versioning and comparison features
  • ✅ Creates Active Learning pipelines
  • ✅ Seamless workflow integration
  • ✅ Comprehensive active learning platform
  • ✅ Cloud storage integration
  • ✅ Integration with MLOps tools
  • ✅ Model explainability reports
  • ✅ Automated robustness tests
  • ✅ Supports visual data search

Pricing

Free to use

Rating & Reviews

3/5 stars based on 1 reviews

Categories & Tags

Category: Data Analysis

Tags: Computer Vision, Model Evaluation, Data Curation, Active Learning, AI Testing, AI Validation

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