Search Results for "data.6bin"

Data annotator for machine learning allows you to centrally create, manage and administer annotation projects for machine learning. Data Annotator for Machine Learning (DAML) is an application that helps machine learning teams facilitate the creation and management of annotations. Active learning with uncertain sampling to query unlabeled data.

...Support for multiple data types including images, audio, text, HTML, time-series, and video.

The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact. You are one of the people we've built refinery for. refinery helps you to build better NLP models in a data-centric approach. Semi-automate your labeling, find low-quality subsets in your training data, and monitor your data in one place. refinery doesn't get rid of manual labeling, but it makes sure that your valuable time is spent well. ...

...Argilla is free, open-source, and 100% compatible with major NLP libraries (Hugging Face transformers, spaCy, Stanford Stanza, Flair, etc.). In fact, you can use and combine your preferred libraries without implementing any specific interface. Most annotation tools treat data collection as a one-off activity at the beginning of each project. In real-world projects, data collection is a key activity of the iterative process of ML model development. Once a model goes into production, you want to monitor and analyze its predictions, and collect more data to improve your model over time. Argilla is designed to close this gap, enabling you to iterate as much as you need.

The Java software Discourse Network Analyzer (DNA) is a qualitative content analysis tool with network export facilities. You import text files and annotate statements that persons or organizations make, and the program will return network matrices of actors connected by shared concepts.

An open-source no-code system for text annotation and building text classifiers. No AI knowledge needed. From task definition to working model in just a few hours! While domain experts label their data, Label Sleuth automatically trains in the background-appropriate machine learning models. To avoid wasted labeling effort, Label Sleuth employs active learning techniques to guide the user in what they should be labeled next. Domain experts can quickly start labeling their data through an intuitive user interface. Developed by researchers across industry and academia, Label Sleuth incorporates the latest research from human-computer interaction, natural language processing, and artificial intelligence. ...

This tool allows the user to annotate by coloring portions of the text. This can be seen as a simple model of annotation. This tool has been built to complete particular experimentation on student behavior (annotation per example) facing particularly difficult content. We put it here as an open-source project.

It is a tool for automatically annotating mentions of DBpedia resources in text, providing a solution for linking unstructured information sources to the Linked Open Data cloud through DBpedia. With a four step approach, DBpedia Spotlight performs named entity extraction, including entity detection and name resolution. It can also be used for named entity recognition, amongst other information extraction tasks. Empower the user experience reusing, interlinking and making semantic queries among high-quality open datasets, extracting meaning from unstructured data.

A GUI-based text annotation tool for creating and visualizing annotations. It uses a flexible stand-off XML data format, and has advanced and customizable methods for information and relation visualization.